Venatrix

venatrix

Stand Out From Other Developers By Contributing to Open Source

التميز عن المطورين الآخرين من خلال المساهمة في المصدر المفتوح

Destaque entre otros desarrolladores contribuyendo al código abierto

Istaknite se od drugih programera doprinoseći otvorenom kodu

Tűnjön ki a többi fejlesztő közül azáltal, hogy hozzájárul a nyílt forráskódhoz

オープンソースに貢献して他の開発者より目立つ

ឈរចេញពីអ្នកអភិវឌ្ឍន៍ផ្សេងទៀតដោយការរួមចំណែកដល់ប្រភពបើកចំហ

Издвојте се од другите програмери со тоа што придонесувате за софтвер со отворен код

Wyróżnij się spośród innych programistów, przyczyniając się do rozwoju oprogramowania typu Open Source

د خلاصې سرچینې سره د مرستې له لارې د نورو پراختیا کونکو څخه ودریږئ

Ieșiți în evidență față de alți dezvoltatori, contribuind la Open Source

Hagarara Mubandi Bateza Imbere Mugutanga Inkomoko

Stick ut från andra utvecklare genom att bidra till öppen källkod

Authors:
(1) Shadab Ahamed, University of British Columbia, Vancouver, BC, Canada, BC Cancer Research Institute, Vancouver, BC, Canada. He was also a Mitacs Accelerate Fellow (May 2022 - April 2023) with Microsoft AI for Good Lab, Redmond, WA, USA (e-mail: shadabahamed1996@gmail.com);
(2) Yixi Xu, Microsoft AI for Good Lab, Redmond, WA, USA;
(3) Claire Gowdy, BC Children’s Hospital, Vancouver, BC, Canada;
(4) Joo H. O, St. Mary’s Hospital, Seoul, Republic of Korea;
(5) Ingrid Bloise, BC Cancer, Vancouver, BC, Canada;
(6) Don Wilson, BC Cancer, Vancouver, BC, Canada;
(7) Patrick Martineau, BC Cancer, Vancouver, BC, Canada;
(8) Franc¸ois Benard, BC Cancer, Vancouver, BC, Canada;
(9) Fereshteh Yousefirizi, BC Cancer Research Institute, Vancouver, BC, Canada;
(10) Rahul Dodhia, Microsoft AI for Good Lab, Redmond, WA, USA;
(11) Juan M. Lavista, Microsoft AI for Good Lab, Redmond, WA, USA;
(12) William B. Weeks, Microsoft AI for Good Lab, Redmond, WA, USA;
(13) Carlos F. Uribe, BC Cancer Research Institute, Vancouver, BC, Canada, and University of British Columbia, Vancouver, BC, Canada;
(14) Arman Rahmim, BC Cancer Research Institute, Vancouver, BC, Canada, and University of British Columbia, Vancouver, BC, Canada. Table of Links Abstract and Intro
Related Work
Materials and Methods
Results
Discussion
Conclusion and References VI. CONCLUSION In this study, we assessed various neural network architectures for automating lymphoma lesion segmentation in PET/CT images across multiple datasets. We examined the reproducibility of lesion measures, revealing differences among networks, highlighting their suitability for specific clinical uses. Additionally, we introduced three lesion detection criteria to assess network performance at a per-lesion level, emphasizing their clinical relevance. Lastly, we discussed challenges related to ground truth consistency and stressed the importance of having well-defined protocol for segmentation. This work provides valuable insights into deep learning’s potentials and limitations in lymphoma lesion segmentation and emphasizes the need for standardized annotation practices to enhance research validity and clinical applications. REFERENCES [1] S. F. Barrington et al. “FDG PET for therapy monitoring in Hodgkin and non-Hodgkin lymphomas”. In: European Journal of Nuclear Medicine and Molecular Imaging 44.1 (Aug. 2017), pp. 97–110. ISSN: 1619- 7089. [2] K. Okuyucu et al. “Prognosis estimation under the light of metabolic tumor parameters on initial FDG-PET/CT in patients with primary extranodal lymphoma”. en. In: Radiol. Oncol. 50.4 (Dec. 2016), pp. 360–369. [3] N. Wu et al. “Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening”. In: IEEE Transactions on Medical Imaging 39.4 (2020), pp. 1184–1194. [4] C. Yuan et al. “Diffuse large B-cell lymphoma segmentation in PET-CT images via hybrid learning for feature fusion”. In: Medical Physics 48.7 (2021), pp. 3665– 3678. [5] H. Hu et al. “Lymphoma Segmentation in PET Images Based on Multi-view and Conv3D Fusion Strategy”. In: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). 2020, pp. 1197–1200. [6] H. Li et al. “DenseX-Net: An End-to-End Model for Lymphoma Segmentation in Whole-Body PET/CT Images”. In: IEEE Access 8 (2020), pp. 8004–8018. [7] L. Liu et al. “Improved Multi-modal Patch Based Lymphoma Segmentation with Negative Sample Augmentation and Label Guidance on PET/CT Scans”. In: Multiscale Multimodal Medical Imaging. Ed. by X. Li et al. Cham: Springer Nature Switzerland, 2022, pp. 121–129. ISBN: 978-3-031-18814-5. [8] C. S. Constantino et al. “Evaluation of Semiautomatic and Deep Learning–Based Fully Automatic Segmentation Methods on [18F]FDG PET/CT Images from Patients with Lymphoma: Influence on Tumor Characterization”. In: Journal of Digital Imaging 36.4 (Aug. 2023), pp. 1864–1876. ISSN: 1618-727X. [9] A. J. Weisman et al. “Comparison of 11 automated PET segmentation methods in lymphoma”. English. In: Physics in medicine & biology 65.23 (2020), pp. 235019–235019. [10] A. J. Weisman et al. “Convolutional Neural Networks for Automated PET/CT Detection of Diseased Lymph Node Burden in Patients with Lymphoma”. In: Radiology: Artificial Intelligence 2.5 (2020), e200016. [11] C. Jiang et al. “Deep learning–based tumour segmentation and total metabolic tumour volume prediction in the prognosis of diffuse large B-cell lymphoma patients in 3D FDG-PET images”. In: European Radiology 32.7 (July 2022), pp. 4801–4812. ISSN: 1432-1084. [12] P. Blanc-Durand et al. “Fully automatic segmentation of diffuse large B cell lymphoma lesions on 3D FDGPET/CT for total metabolic tumour volume prediction using a convolutional neural network.” In: European Journal of Nuclear Medicine and Molecular Imaging 48.5 (May 2021), pp. 1362–1370. ISSN: 1619-7089. [13] S. Ahamed et al. “A U-Net Convolutional Neural Network with Multiclass Dice Loss for Automated Segmentation of Tumors and Lymph Nodes from Head and Neck Cancer PET/CT Images”. In: Head and Neck Tumor Segmentation and Outcome Prediction. Ed. by V. Andrearczyk et al. Cham: Springer Nature Switzerland, 2023, pp. 94–106. ISBN: 978-3-031-27420-6. [14] S. Gatidis et al. “A whole-body FDG-PET/CT Dataset with manually annotated Tumor Lesions”. In: Scientific Data 9.1 (Oct. 2022), p. 601. ISSN: 2052-4463. [15] M. Pop et al. “Left-Ventricle Quantification Using Residual U-Net”. English. In: vol. 11395. Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges. Switzerland: Springer International Publishing AG, 2019, pp. 371–380. ISBN: 0302-9743. [16] A. Myronenko. “3D MRI Brain Tumor Segmentation Using Autoencoder Regularization”. English. In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. Cham: Springer International Publishing, 2019, pp. 311–320. ISBN: 0302-9743. [17] F. Isensee et al. “nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation”. In: Nature Methods 18.2 (Dec. 2020), pp. 203–211. [18] A. Hatamizadeh et al. “Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images”. English. In: (2022). [19] M. J. Cardoso et al. MONAI: An open-source framework for deep learning in healthcare. 2022. arXiv: 2211. 02701 [cs.LG]. [20] S. Ahamed et al. “Towards enhanced lesion segmentation using a 3D neural network trained on multiresolution cropped patches of lymphoma PET images”. In: Journal of Nuclear Medicine 64.supplement 1 (2023), P1360–P1360. ISSN: 0161-5505. [21] J. L. Fleiss. “Measuring nominal scale agreement among many raters”. English. In: Psychological bulletin 76.5 (1971), pp. 378–382. [22] A. K. Jha et al. “Nuclear Medicine and artificial intelligence: Best practices for evaluation (the RELAINCE guidelines)”. en. In: J. Nucl. Med. 63.9 (Sept. 2022), pp. 1288–1299. [23] N. Hasani et al. “Artificial Intelligence in Lymphoma PET Imaging: A Scoping Review (Current Trends and Future Directions)”. In: PET clinics 17.1 (Jan. 1), pp. 145–174. ISSN: 1556-8598. [24] S. K. Warfield et al. “Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation”. en. In: IEEE Trans. Med. Imaging 23.7 (July 2004), pp. 903–921. This paper is available on arxiv under CC 4.0 license. Authors: (1) Shadab Ahamed, University of British Columbia, Vancouver, BC, Canada, BC Cancer Research Institute, Vancouver, BC, Canada. He was also a Mitacs Accelerate Fellow (May 2022 - April 2023) with Microsoft AI for Good Lab, Redmond, WA, USA (e-mail: shadabahamed1996@gmail.com); (2) Yixi Xu, Microsoft AI for Good Lab, Redmond, WA, USA; (3) Claire Gowdy, BC Children’s Hospital, Vancouver, BC, Canada; (4) Joo H. O, St. Mary’s Hospital, Seoul, Republic of Korea; (5) Ingrid Bloise, BC Cancer, Vancouver, BC, Canada; (6) Don Wilson, BC Cancer, Vancouver, BC, Canada; (7) Patrick Martineau, BC Cancer, Vancouver, BC, Canada; (8) Franc¸ois Benard, BC Cancer, Vancouver, BC, Canada; (9) Fereshteh Yousefirizi, BC Cancer Research Institute, Vancouver, BC, Canada; (10) Rahul Dodhia, Microsoft AI for Good Lab, Redmond, WA, USA; (11) Juan M. Lavista, Microsoft AI for Good Lab, Redmond, WA, USA; (12) William B. Weeks, Microsoft AI for Good Lab, Redmond, WA, USA; (13) Carlos F. Uribe, BC Cancer Research Institute, Vancouver, BC, Canada, and University of British Columbia, Vancouver, BC, Canada; (14) Arman Rahmim, BC Cancer Research Institute, Vancouver, BC, Canada, and University of British Columbia, Vancouver, BC, Canada. Authors: Authors: (1) Shadab Ahamed, University of British Columbia, Vancouver, BC, Canada, BC Cancer Research Institute, Vancouver, BC, Canada. He was also a Mitacs Accelerate Fellow (May 2022 - April 2023) with Microsoft AI for Good Lab, Redmond, WA, USA (e-mail: shadabahamed1996@gmail.com); (2) Yixi Xu, Microsoft AI for Good Lab, Redmond, WA, USA; (3) Claire Gowdy, BC Children’s Hospital, Vancouver, BC, Canada; (4) Joo H. O, St. Mary’s Hospital, Seoul, Republic of Korea; (5) Ingrid Bloise, BC Cancer, Vancouver, BC, Canada; (6) Don Wilson, BC Cancer, Vancouver, BC, Canada; (7) Patrick Martineau, BC Cancer, Vancouver, BC, Canada; (8) Franc¸ois Benard, BC Cancer, Vancouver, BC, Canada; (9) Fereshteh Yousefirizi, BC Cancer Research Institute, Vancouver, BC, Canada; (10) Rahul Dodhia, Microsoft AI for Good Lab, Redmond, WA, USA; (11) Juan M. Lavista, Microsoft AI for Good Lab, Redmond, WA, USA; (12) William B. Weeks, Microsoft AI for Good Lab, Redmond, WA, USA; (13) Carlos F. Uribe, BC Cancer Research Institute, Vancouver, BC, Canada, and University of British Columbia, Vancouver, BC, Canada; (14) Arman Rahmim, BC Cancer Research Institute, Vancouver, BC, Canada, and University of British Columbia, Vancouver, BC, Canada. Table of Links Abstract and Intro Related Work Materials and Methods Results Discussion Conclusion and References Abstract and Intro Abstract and Intro Related Work Related Work Materials and Methods Materials and Methods Results Results Discussion Discussion Conclusion and References Conclusion and References VI. CONCLUSION In this study, we assessed various neural network architectures for automating lymphoma lesion segmentation in PET/CT images across multiple datasets. We examined the reproducibility of lesion measures, revealing differences among networks, highlighting their suitability for specific clinical uses. Additionally, we introduced three lesion detection criteria to assess network performance at a per-lesion level, emphasizing their clinical relevance. Lastly, we discussed challenges related to ground truth consistency and stressed the importance of having well-defined protocol for segmentation. This work provides valuable insights into deep learning’s potentials and limitations in lymphoma lesion segmentation and emphasizes the need for standardized annotation practices to enhance research validity and clinical applications. REFERENCES [1] S. F. Barrington et al. “FDG PET for therapy monitoring in Hodgkin and non-Hodgkin lymphomas”. In: European Journal of Nuclear Medicine and Molecular Imaging 44.1 (Aug. 2017), pp. 97–110. ISSN: 1619- 7089. [2] K. Okuyucu et al. “Prognosis estimation under the light of metabolic tumor parameters on initial FDG-PET/CT in patients with primary extranodal lymphoma”. en. In: Radiol. Oncol. 50.4 (Dec. 2016), pp. 360–369. [3] N. Wu et al. “Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening”. In: IEEE Transactions on Medical Imaging 39.4 (2020), pp. 1184–1194. [4] C. Yuan et al. “Diffuse large B-cell lymphoma segmentation in PET-CT images via hybrid learning for feature fusion”. In: Medical Physics 48.7 (2021), pp. 3665– 3678. [5] H. Hu et al. “Lymphoma Segmentation in PET Images Based on Multi-view and Conv3D Fusion Strategy”. In: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). 2020, pp. 1197–1200. [6] H. Li et al. “DenseX-Net: An End-to-End Model for Lymphoma Segmentation in Whole-Body PET/CT Images”. In: IEEE Access 8 (2020), pp. 8004–8018. [7] L. Liu et al. “Improved Multi-modal Patch Based Lymphoma Segmentation with Negative Sample Augmentation and Label Guidance on PET/CT Scans”. In: Multiscale Multimodal Medical Imaging. Ed. by X. Li et al. Cham: Springer Nature Switzerland, 2022, pp. 121–129. ISBN: 978-3-031-18814-5. [8] C. S. Constantino et al. “Evaluation of Semiautomatic and Deep Learning–Based Fully Automatic Segmentation Methods on [18F]FDG PET/CT Images from Patients with Lymphoma: Influence on Tumor Characterization”. In: Journal of Digital Imaging 36.4 (Aug. 2023), pp. 1864–1876. ISSN: 1618-727X. [9] A. J. Weisman et al. “Comparison of 11 automated PET segmentation methods in lymphoma”. English. In: Physics in medicine & biology 65.23 (2020), pp. 235019–235019. [10] A. J. Weisman et al. “Convolutional Neural Networks for Automated PET/CT Detection of Diseased Lymph Node Burden in Patients with Lymphoma”. In: Radiology: Artificial Intelligence 2.5 (2020), e200016. [11] C. Jiang et al. “Deep learning–based tumour segmentation and total metabolic tumour volume prediction in the prognosis of diffuse large B-cell lymphoma patients in 3D FDG-PET images”. In: European Radiology 32.7 (July 2022), pp. 4801–4812. ISSN: 1432-1084. [12] P. Blanc-Durand et al. “Fully automatic segmentation of diffuse large B cell lymphoma lesions on 3D FDGPET/CT for total metabolic tumour volume prediction using a convolutional neural network.” In: European Journal of Nuclear Medicine and Molecular Imaging 48.5 (May 2021), pp. 1362–1370. ISSN: 1619-7089. [13] S. Ahamed et al. “A U-Net Convolutional Neural Network with Multiclass Dice Loss for Automated Segmentation of Tumors and Lymph Nodes from Head and Neck Cancer PET/CT Images”. In: Head and Neck Tumor Segmentation and Outcome Prediction. Ed. by V. Andrearczyk et al. Cham: Springer Nature Switzerland, 2023, pp. 94–106. ISBN: 978-3-031-27420-6. [14] S. Gatidis et al. “A whole-body FDG-PET/CT Dataset with manually annotated Tumor Lesions”. In: Scientific Data 9.1 (Oct. 2022), p. 601. ISSN: 2052-4463. [15] M. Pop et al. “Left-Ventricle Quantification Using Residual U-Net”. English. In: vol. 11395. Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges. Switzerland: Springer International Publishing AG, 2019, pp. 371–380. ISBN: 0302-9743. [16] A. Myronenko. “3D MRI Brain Tumor Segmentation Using Autoencoder Regularization”. English. In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. Cham: Springer International Publishing, 2019, pp. 311–320. ISBN: 0302-9743. [17] F. Isensee et al. “nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation”. In: Nature Methods 18.2 (Dec. 2020), pp. 203–211. [18] A. Hatamizadeh et al. “Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images”. English. In: (2022). [19] M. J. Cardoso et al. MONAI: An open-source framework for deep learning in healthcare. 2022. arXiv: 2211. 02701 [cs.LG]. [20] S. Ahamed et al. “Towards enhanced lesion segmentation using a 3D neural network trained on multiresolution cropped patches of lymphoma PET images”. In: Journal of Nuclear Medicine 64.supplement 1 (2023), P1360–P1360. ISSN: 0161-5505. [21] J. L. Fleiss. “Measuring nominal scale agreement among many raters”. English. In: Psychological bulletin 76.5 (1971), pp. 378–382. [22] A. K. Jha et al. “Nuclear Medicine and artificial intelligence: Best practices for evaluation (the RELAINCE guidelines)”. en. In: J. Nucl. Med. 63.9 (Sept. 2022), pp. 1288–1299. [23] N. Hasani et al. “Artificial Intelligence in Lymphoma PET Imaging: A Scoping Review (Current Trends and Future Directions)”. In: PET clinics 17.1 (Jan. 1), pp. 145–174. ISSN: 1556-8598. [24] S. K. Warfield et al. “Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation”. en. In: IEEE Trans. Med. Imaging 23.7 (July 2004), pp. 903–921. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv available on arxiv

Deep Neural Networks to Detect and Quantify Lymphoma Lesions: Conclusion and References

ডিপ নিউরাল নেটওয়ার্ক লিম্ফোমা ক্ষত সনাক্ত এবং পরিমাপ করার জন্য: উপসংহার এবং রেফারেন্স

Tiefe neuronale Netzwerke zur Erkennung und Quantifizierung von Lymphomläsionen: Schlussfolgerung und Referenzen

Redes neuronales profundas para detectar y cuantificar lesiones de linfoma: conclusiones y referencias

Réseaux de neurones profonds pour détecter et quantifier les lésions de lymphome : conclusion et références

लिम्फोमा घावों का पता लगाने और मात्रा निर्धारित करने के लिए डीप न्यूरल नेटवर्क: निष्कर्ष और संदर्भ

リンパ腫病変の検出と定量化のためのディープニューラルネットワーク：結論と参考文献

림프종 병변을 검출하고 정량화하기 위한 심층 신경망: 결론 및 참고 문헌

Redes Neurais Profundas para Detectar e Quantificar Lesões de Linfoma: Conclusão e Referências

Глубокие нейронные сети для обнаружения и количественной оценки поражений лимфомой: заключение и ссылки

Lenfoma Lezyonlarını Tespit Etmek ve Ölçmek İçin Derin Sinir Ağları: Sonuç ve Referanslar

Mạng lưới thần kinh sâu để phát hiện và định lượng tổn thương ung thư hạch: Kết luận và tài liệu tham khảo

深度神经网络检测和量化淋巴瘤病变：结论和参考文献

One of the most effective ways to cultivate an engaged and productive team is to actively demonstrate appreciation for your employees’ hard work and dedication. When individuals feel genuinely valued by their employer, it translates into improved morale, heightened job satisfaction, increased productivity, and greater overall retention. Showing genuine gratitude doesn't have to be an elaborate or costly endeavor. Even seemingly simple yet thoughtful gestures can go a long way in making your staff feel recognized and energized about their contributions to the company. Whether through personalized acknowledgments, unique incentives, or fostering a strong sense of community, there are myriad creative approaches to expressing appreciation. Personalized recognition A simple but powerful way to make employees feel appreciated is through personalized recognition of their efforts. According to Asim Hafeez, Owner and Operator of Empower Energy Solutions, “Showing your employees that you genuinely care through personal gestures that recognize their value and contributions resonates deeply.” This recognition can be as easy as direct, one-on-one praise or a handwritten thank-you note acknowledging specific contributions. Whatever approach you take, make sure to tell your employees face-to-face that they are doing well. Public recognition is also highly impactful. “Recognizing employees' achievements in team meetings or through company-wide communications makes them feel valued and seen by their peers and the broader organization,” says Amanda Webster, vice president of Fund & Grow. Simple acts like announcing an “Employee of the Month” or giving shout-outs during meetings can motivate individuals and foster a culture of collaboration. Team building and community Creating a strong sense of community and team cohesion is another way to make employees feel truly part of something bigger. “Organize events that allow employees to relax and bond outside work, such as team dinners, outings, or recreational activities,” Webster suggests. “These events can enhance team cohesion and make everyone feel like part of a community.” Jay Avigdor, CEO and president of Velocity Capital Group, takes this principle even further by striving to build a truly family-like atmosphere. “Everyone here is far more than an employee — we're all family,” he says. “Team-building activities, outings, and fostering an authentic sense of belonging will pay dividends in productivity and retention efforts.” Professional development opportunities Investing in both your employees’ professional and personal growth demonstrates a vested interest in their long-term success. “I can’t stress enough how everything stems from genuine care,” Hafeez notes. “Investing in your employees’ personal growth and professional development shows that you care, and they will be more willing to offer the same care right back into your company.” For example, Webster states, “Investing in your employees' growth by providing training, workshops, or courses shows that you value their development and future.” However, providing learning opportunities is only one facet. “Consistent feedback and open communication are essential,” says Asha Tarry, a licensed psychotherapist, caregiver coach, and owner of Behavioral Health Consulting Services LMSW, PLLC. “Employees like periodic updates on their work performance because it allows them to take inventory of themselves and set short-term goals they can review with their managers.” As Tarry explains, this dialogue allows employees to gain clarity on expectations and voice any needs for further training or support. It also facilitates an environment where growth is prioritized and shows you are actively invested in their professional journeys. Unique incentives and perks Creative incentives and fun workplace perks can infuse excitement and tangible rewards into your appreciation efforts. Avigdor, for example, utilizes an innovative “spinning wheel” system. “The more we fund, the more spins they get,” Avigdor explains. “For every $1 million we fund, the team gets a spin at the end of the month for items like new Airpods, cash prizes of $150 or $200, mystery prizes, and gift cards. If we fund more, it means they’ve worked harder, and the more spins they get.” Avigdor goes on to describe additional creative perks at his company. “One day, we had breakfast that came to the office with an omelet chef and a guy who makes professional espressos,” he says. “We even shut down the office once early and had a ventriloquist come for some entertainment!” Other ideas include office treats, creative spaces to recharge, or unique team bonuses. Showing genuine care At the core of any effective appreciation strategy is genuine care and interest in your employees as whole individuals. Hafeez suggests asking questions like, “When was the last time we asked them what their dreams were? When was the last time we had them submit a list of their dreams and followed up with them?” Finding ways to add value to employees' lives outside of work, whether funding a class they're interested in or connecting them to resources, shows that you see them as multidimensional people. “I think that's where the good stuff comes in — when we take genuine interest in adding value to their lives outside,” Hafeez says. Equally important is leading with empathy and consideration. “Being a considerate and respectful speaker had an impact on my self-esteem and performance,” Tarry reflects. “It created more anxiety not only in me, but I saw it firsthand in my colleagues. Conversely, when I worked with managers who were ‘people leaders,’ my mood was better.” When fostering a culture of appreciation within your organization, it’s clear that the simplest gestures often yield the most significant impact. Whether through personalized acknowledgments, fostering a strong sense of community, or investing in professional growth, the key lies in demonstrating genuine care for your employees. By recognizing and celebrating their contributions publicly and privately, you can boost morale and cultivate a sense of belonging and camaraderie. Furthermore, providing opportunities for growth and development, along with creative incentives and perks, reinforces your commitment to their success and well-being. Ultimately, leading with empathy and consideration establishes a foundation of trust and support, paving the way for a motivated and engaged workforce. This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author One of the most effective ways to cultivate an engaged and productive team is to actively demonstrate appreciation for your employees’ hard work and dedication. When individuals feel genuinely valued by their employer, it translates into improved morale, heightened job satisfaction, increased productivity, and greater overall retention. Showing genuine gratitude doesn't have to be an elaborate or costly endeavor. Even seemingly simple yet thoughtful gestures can go a long way in making your staff feel recognized and energized about their contributions to the company. Whether through personalized acknowledgments, unique incentives, or fostering a strong sense of community, there are myriad creative approaches to expressing appreciation. Personalized recognition Personalized recognition A simple but powerful way to make employees feel appreciated is through personalized recognition of their efforts. According to Asim Hafeez, Owner and Operator of Empower Energy Solutions , “Showing your employees that you genuinely care through personal gestures that recognize their value and contributions resonates deeply.” Empower Energy Solutions Empower Energy Solutions This recognition can be as easy as direct, one-on-one praise or a handwritten thank-you note acknowledging specific contributions. Whatever approach you take, make sure to tell your employees face-to-face that they are doing well. Public recognition is also highly impactful. “Recognizing employees' achievements in team meetings or through company-wide communications makes them feel valued and seen by their peers and the broader organization,” says Amanda Webster, vice president of Fund & Grow . Simple acts like announcing an “Employee of the Month” or giving shout-outs during meetings can motivate individuals and foster a culture of collaboration. Fund & Grow Fund & Grow Team building and community Team building and community Creating a strong sense of community and team cohesion is another way to make employees feel truly part of something bigger. “Organize events that allow employees to relax and bond outside work, such as team dinners, outings, or recreational activities,” Webster suggests. “These events can enhance team cohesion and make everyone feel like part of a community.” Jay Avigdor, CEO and president of Velocity Capital Group , takes this principle even further by striving to build a truly family-like atmosphere. “Everyone here is far more than an employee — we're all family,” he says. “Team-building activities, outings, and fostering an authentic sense of belonging will pay dividends in productivity and retention efforts.” Velocity Capital Group Velocity Capital Group Professional development opportunities Professional development opportunities Investing in both your employees’ professional and personal growth demonstrates a vested interest in their long-term success. “I can’t stress enough how everything stems from genuine care,” Hafeez notes. “Investing in your employees’ personal growth and professional development shows that you care, and they will be more willing to offer the same care right back into your company.” For example, Webster states, “Investing in your employees' growth by providing training, workshops, or courses shows that you value their development and future.” However, providing learning opportunities is only one facet. “Consistent feedback and open communication are essential,” says Asha Tarry, a licensed psychotherapist, caregiver coach, and owner of Behavioral Health Consulting Services LMSW, PLLC. “Employees like periodic updates on their work performance because it allows them to take inventory of themselves and set short-term goals they can review with their managers.” As Tarry explains, this dialogue allows employees to gain clarity on expectations and voice any needs for further training or support. It also facilitates an environment where growth is prioritized and shows you are actively invested in their professional journeys. Unique incentives and perks Unique incentives and perks Creative incentives and fun workplace perks can infuse excitement and tangible rewards into your appreciation efforts. Avigdor, for example, utilizes an innovative “spinning wheel” system. “The more we fund, the more spins they get,” Avigdor explains. “For every $1 million we fund, the team gets a spin at the end of the month for items like new Airpods, cash prizes of $150 or $200, mystery prizes, and gift cards. If we fund more, it means they’ve worked harder, and the more spins they get.” Avigdor goes on to describe additional creative perks at his company. “One day, we had breakfast that came to the office with an omelet chef and a guy who makes professional espressos,” he says. “We even shut down the office once early and had a ventriloquist come for some entertainment!” Other ideas include office treats, creative spaces to recharge, or unique team bonuses. Showing genuine care Showing genuine care At the core of any effective appreciation strategy is genuine care and interest in your employees as whole individuals. Hafeez suggests asking questions like, “When was the last time we asked them what their dreams were? When was the last time we had them submit a list of their dreams and followed up with them?” Finding ways to add value to employees' lives outside of work, whether funding a class they're interested in or connecting them to resources, shows that you see them as multidimensional people. “I think that's where the good stuff comes in — when we take genuine interest in adding value to their lives outside,” Hafeez says. Equally important is leading with empathy and consideration. “Being a considerate and respectful speaker had an impact on my self-esteem and performance,” Tarry reflects. “It created more anxiety not only in me, but I saw it firsthand in my colleagues. Conversely, when I worked with managers who were ‘people leaders,’ my mood was better.” When fostering a culture of appreciation within your organization, it’s clear that the simplest gestures often yield the most significant impact. Whether through personalized acknowledgments, fostering a strong sense of community, or investing in professional growth, the key lies in demonstrating genuine care for your employees. By recognizing and celebrating their contributions publicly and privately, you can boost morale and cultivate a sense of belonging and camaraderie. Furthermore, providing opportunities for growth and development, along with creative incentives and perks, reinforces your commitment to their success and well-being. Ultimately, leading with empathy and consideration establishes a foundation of trust and support, paving the way for a motivated and engaged workforce. This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author https://business.hackernoon.com/brand-as-author

Empowering Your Team: 5 Easy Ways To Show Employee Appreciation

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It's become blatantly apparent to seasoned readers and writers that AI is pulling the strings behind the scenes, and it's like trying to pass off a synthetic rose as the real deal. There's a certain artificiality, a lack of genuine human touch that leaves a discerning reader feeling, well, duped. Let’s not beat around the bush here. Using like write content such as a blog post is like trying to replace Shakespeare with a computer program that generates words from billions of sentences based on known patterns. ChatGPT to do things Sure, it can pull coherent sentences, though it lacks the spirit, the enthusiasm, the creativity that a human writer brings to the table. And don't even get me started on trying to trick readers into thinking it's all man-made. With AI content publishers on the rise, this is a game of cat and mouse. The AI ​​tries to mimic human expression, and the detector tries to reveal some cool algorithm calculated underneath. It’s a battle of wits, and honestly, it’s like cheap magic with the audience knowing exactly how the rabbit got into the hat. Now, as we stand on the precipice of 2024, there is a tiny glimmer of hope (or fear, depending on your point of view) Could we witness the birth of an AI Shakespeare, a digital Dickens? The color blew my mind. Call me a Luddite, but in the mess of human creativity there are imperfections and flaws that make text uniquely ours. Let’s get into the details. Using ChatGPT in text processing and content creation feels like serving good old-fashioned wine and then revealing that it is in fact non-alcoholic beverage. It’s not just the words on the page; it’s the soul, the idiosyncrasies, the very human nuances that gives life to a story. ChatGPT, for all its wonders and algorithmic ingenuity, cannot replicate the intricate tapestry of human commentary or creativity. It’s nothing more than a digital ventriloquist trying to mimic the rhythm of a professional speaker, and the audience doesn’t pick up a whisper of the strings being pulled. So, here’s to a brave new world of AI content creation. May 2024 not be the year of proving us wrong or solidifying our belief that, no matter how brilliant algorithms are, they will never have the warmth and authenticity of a human-authored story. Cheers to the writers, dreamers’ storytellers and tech experts here on – those who put real life into words and provide us with the entertainment and quality content consumption we seek. Id also like to say a big thank you to for birthing this great platform. Hackernoon David Smooke Have a happy and safe 2024!

The State of Content Creation in the Age of Artificial Intelligence

HYDRAULIC MACHINERY.

SENSATION AND PERCEPTION.

ON THE CARE OF HEALTH.

We've all faced that stubborn coding challenge where you just feel stuck and drained of ideas. Or, worse, the general malaise of burnout that saps all inspiration from your work... where instead of getting energy from what we're working on, it just takes and takes and takes. Reigniting creative energy takes effort but pays off in big ways. We have to remember that “busy” does not equate to “productive.” Sometimes, the relentless pace of the work gives the illusion of constant productivity. But exhaustion breeds staleness and clouds the mind -- in other words, you end up getting in your own way. Over the years, I've come across a few strategies that help me refuel; maybe you'll find use in one or two. Step Away and Detach Build in time off to physically and mentally detach from work. Coding requires mental focus. Our brains need periods of rest to process ideas subconsciously. This should not be left to vacations. This is a throughout-the-day thing. Take breaks. Stand up! Get some sunshine! intense When it comes to vacations, completely detach. Avoid anything code-related—Immerse in totally different activities instead. Make rest non-negotiable. You’ll return with renewed perspective and fresh approaches to work -- and, sometimes, life in general! Immerse in a New Domain Look outside coding to unrelated domains for inspiration. New spaces provide new metaphors and mental models to draw from. Scan broadly at first to glimpse various ideas. Follow whatever domain intrigues you deeper. The fresh context will stimulate creativity. Have you ever stopped to really look at how plants grow? I mean, really?! The material phase shifting necessary for them to move around and grow is completely insanely interesting. And how vines wave around in circles as if "looking" for something to grab onto. Or, how about the fractalized growth patterns in plants: dendritic venation? This dendritic venation is a wonderful physical manifestation of modularity and a demonstration of the ability of simple structures to manifest an incredible amount of complexity. It's not necessary for solutions to be complex to manifest complex behavior. obviously The proof is right there! Change Your Environment Get into different physical environments to spark new associations. Work from a coffee shop or take a nature retreat. Different spaces provoke different energies and ideas. Being in one place too long for any reason breeds staleness. Dislodge your thoughts by changing the scenery. Collaborate and Gather Diverse Input Discuss challenges with colleagues across disciplines. Their perspectives will reveal blindspots in your thinking. Feedback and co-creation generate new directions. It's amazing how much clarity is derived from the process of simplifying and abstracting ideas from software such that they can be understood and discussed with folks outside of software. It's worth the effort! Bounce half-formed ideas off mentors. The interplay of voices brings out your best ideas. You have all you need inside already - collaborate to pull it out. Make Side Projects Passion Projects Reignite the sheer love of coding with no strings attached. Experiment freely with new technologies that excite you. Follow passion projects where they lead naturally. Feel free to make things! useless Coding without creative constraints reconnects you with the joy of programming. Rejuvenate by scratching your experimentation itch. Of all the things on this list, finding a way to feel like you can with your profession is by far the most important. play Limit Distractions and Context Switching Constant distractions and context switching impede deep focus and flow states. Limit distractions during heads-down work. Block time to dive fully into complex problems. Put it on the calendar, AND . tell people that you're unavailable It's way too easy to say "yes" to things. We all want to be helpful. It feels good to always be available to jump in and help everyone else. But you have to be able to take care of yourself, too. Don't leave yourself to the end. Start there. Depth breeds unexpected connections as ideas intermingle. Shallow work prevents those sparks. Remove disruptions and focus deeply. Reflect on Past Successes Remember projects where you felt fully engaged in flow. Analyze what conditions and choices worked well. Then, recreate those situations. Review code from your creative peaks. Recall the mindset you brought to the work. Recapture the essence and apply it again. Creativity requires renewal. While demanding, make recharging a priority. Your inspiration fuels your passion for programming itself—experiment and find what works for you. Invest in yourself. You're worth it. Also published . here

Reviving Your Creative Energy as a Developer

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Stories, News & Mentions about VENATRIX

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