A Proposal for a New Python Library Implementing Stepwise Procedure by Luiz Paulo Fávero, Helder Prado Santos, Patrícia Belfiore, Alexandre Duarte, Igor Pinheiro de Araújo Costa, Adilson Vilarinho Terra, Miguel Ângelo Lellis Moreira, Wilson Tarantin Junior, Marcos dos Santos

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Precision‐Optimised Post‐Stroke Prognoses by Thomas M. H. Hope, Howard Bowman, Rachel M. Bruce, Alex P. Leff, Cathy J. Price

“…Researchers have sought to bridge this gap by treating the post‐stroke prognostic problem as a machine learning problem, reporting prediction error metrics across samples of patients whose outcomes are known. …”
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A disentangled generative model for improved drug response prediction in patients via sample synthesis by Kunshi Li, Bihan Shen, Fangyoumin Feng, Xueliang Li, Yue Wang, Na Feng, Zhixuan Tang, Liangxiao Ma, Hong Li

“…Personalized drug response prediction from molecular data is an important challenge in precision medicine for treating cancer. Computational methods have been widely explored and have become increasingly accurate in recent years. …”
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Individualized functional brain mapping machine learning prediction of symptom-change resulting from selective kappa-opioid antagonism in an anhedonic sample from a Fast-Fail trial by Matthew D. Sacchet, Joseph L. Valenti, Poorvi Keshava, Shane W. Walsh, Moria J. Smoski, Andrew D. Krystal, Diego A. Pizzagalli

“…Background: Anhedonia remains a difficult-to-treat symptom and has been associated with poor clinical course transdiagnostically. …”
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Deep learning-assisted analysis of biomarker changes after increase of dosing from aflibercept 2 mg to 8 mg in therapy-resistant neovascular age-related macular degeneration by Siegfried Priglinger, Jakob Siedlecki, Benedikt Schworm, Franziska Eckardt, Michael Hafner, Ben Asani, Caspar Liesenhoff, Alexander Kufner, Johannes Benedikt Schiefelbein

“…Since 01/2024, aflibercept 8 mg represents an additional treatment option and contains a four times higher dosage than the already known aflibercept 2 mg.Methods To evaluate the real-world efficacy of aflibercept 8 mg in refractory nAMD patients, focusing on changes in key optical coherence tomography biomarkers over a follow-up period of the first four aflibercept 8 mg injections using a deep learning-based semantic segmentation algorithm. Inclusion criteria were: switch to aflibercept 8 mg after insufficient response to aflibercept 2 mg, marked by persistent retinal fluid or inability to extend treatment beyond 6 weeks; completion of at least 3 months (90 days) follow-up under treat-and-extend treatment regime; and no confounding conditions like intraocular infection, uveitis or other retinal diseases.Results 23 eyes of 21 patients with therapy-resistant nAMD were switched to aflibercept 8 mg. …”
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Harnessing unsupervised machine learning with [18F]FDG PET/CT to develop a composite model for predicting overall survival in cervical cancer patients undergoing concurrent chemora... by Jinyu Shi, Lian Wang, Min Zhou, Shushan Ge, Shushan Ge, Bin Zhang, Jiangqin Han, Jihui Li, Shengming Deng, Shengming Deng

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Automatic extraction of upper-limb kinematic activity using deep learning-based markerless tracking during deep brain stimulation implantation for Parkinson's disease: A proof of c... by Sunderland Baker, Anand Tekriwal, Gidon Felsen, Elijah Christensen, Lisa Hirt, Steven G Ojemann, Daniel R Kramer, Drew S Kern, John A Thompson

“…Optimal placement of deep brain stimulation (DBS) therapy for treating movement disorders routinely relies on intraoperative motor testing for target determination. …”
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The challenging reality of the clinical learning environment at Damascus University Faculty of Dental Medicine in Syria: A qualitative study [version 4; peer review: 1 approved, 3... by Khattab Mustafa, Issam Jamous, Bashar Jazayerli, Ghaith Alfakhry, Khaled Alhomsi

“…In the latter, students engage in treating complex cases as part of their professional training. …”
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Real-world use of an artificial intelligence–powered clinical decision support tool for ovarian stimulation by Cameron J. Bixby, D.O., Bradley Miller, M.D.

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Cellpose as a reliable method for single-cell segmentation of autofluorescence microscopy images by Jeremiah M. Riendeau, Amani A. Gillette, Emmanuel Contreras Guzman, Mario Costa Cruz, Aleksander Kralovec, Shirsa Udgata, Alexa Schmitz, Dustin A. Deming, Beth A. Cimini, Melissa C. Skala

“…These models were applied to PANC-1 cells treated with metabolic inhibitors and patient-derived cancer organoids (9 patients) treated with chemotherapies. …”
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Le compostage, entre réduction des déchets et domestication du pourrissement by Céline Granjou, Marc Higgin, Coralie Mounet

“…Drawing on an empirical investigation into local practices and techniques of composting, our article shows that people who start composting at home do not merely learn to conform to standardized norms to reduce their waste: they also learn a range of new experimental skills and know-how aiming to assess and nourish the processes of decomposition and rotting that take place in their local compost. …”
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Potential Applications and Ethical Considerations for Artificial Intelligence in Traumatic Brain Injury Management by Kryshawna Beard, Ashley M. Pennington, Amina K. Gauff, Kelsey Mitchell, Johanna Smith, Donald W. Marion

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SmartCardio: Advancing cardiac risk prediction through Internet of Things and edge cloud intelligence by S. Durga, Esther Daniel, J. Andrew, Radhakrishna Bhat

“…The integration of Internet of Things (IoT) and deep learning technologies, including transfer learning, has transformed healthcare by improving the prediction and monitoring of conditions such as arrhythmias, which can be fatal if not detected and treated promptly. …”
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Enhanced Classification of Ear Disease Images Using Metaheuristic Feature Selection by Murat Ekinci, Furkancan Demircan, Zafer Cömert, Eyup Gedikli

“…This study aims to evaluate the efficacy of computationally efficient machine learning models in classifying ear disease images. …”
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The Role of Artificial Intelligence in Obesity Risk Prediction and Management: Approaches, Insights, and Recommendations by Lillian Huang, Ellen N. Huhulea, Elizabeth Abraham, Raphael Bienenstock, Esewi Aifuwa, Rahim Hirani, Atara Schulhof, Raj K. Tiwari, Mill Etienne

“…In recent years, artificial intelligence (AI) and machine learning (ML) have emerged as powerful tools in healthcare, offering novel approaches to chronic disease prevention. …”
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Recent advances in pericardium extracellular matrix for tissue regeneration, along with a short insight into artificial intelligence by Parand Shariat Rad, Parand Shariat Rad, Mozafar Khazaei, Mozafar Khazaei, Elham Ghanbari, Mehdi Rashidi, Leila Rezakhani, Leila Rezakhani

“…Medical science is striving to find new solutions to treat various diseases. Tissue engineering with a great potential to develop tissues and even organs from synthetic and biological materials, open a new gate toward absolute treatments. …”
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Early detection of ICU-acquired infections using high-frequency electronic health record data by Meri R. J. Varkila, Giacomo Lancia, Maarten van Smeden, Marc J. M. Bonten, Cristian Spitoni, Olaf L. Cremer

“…Conclusion A dynamic modelling approach that incorporates machine learning of high-frequency vital sign data shows promise as a continuous bedside index of infection risk. …”
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Prognostic correlation analysis of colorectal cancer patients based on monocyte to lymphocyte ratio and folate receptor-positive circulating tumor cells and construction of a machi... by Siying Pan, Chi Lu, Chi Lu, Hongda Lu, Hongda Lu, Hongfeng Zhang

“…PurposeTo evaluate the prognostic value of the monocyte to lymphocyte ratio (MLR) and folate receptor-positive circulating tumor cells (FR+CTCs) in patients with colorectal cancer (CRC) and to develop predictive model for post-treatment survival using machine learning (ML) algorithms.MethodsWe retrospectively analyzed 67 CRC patients treated with radical surgery or chemoradiotherapy at The Central Hospital of Wuhan from January 2020 to December 2022. …”
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Machine learning to identify suitable boundaries for band-pass spectral analysis of dynamic [ $$^{11}$$ 11 C]Ro15-4513 PET scan and voxel-wise parametric map generation by Zeyu Chang, Colm J. McGinnity, Rainer Hinz, Manlin Wang, Joel Dunn, Ruoyang Liu, Mubaraq Yakubu, Paul Marsden, Alexander Hammers

“…Abstract Background Spectral analysis is a model-free PET quantification technique that treats the time-space signal as an impulse response to a bolus injection. …”
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Advancing biomass fermentation and composting for global sustainability: A bibliometric perspective (2019–2024) by Fan Jiao, Xueru Zhu, Chao Li, Haojun Xie, Hua Li

“…Additionally, the integration of advanced technologies, such as artificial intelligence and machine learning, has encouraged scholars to explore intelligent fermentation, offering potential benefits in optimizing product processes and enhancing the prediction and control of product yield and performance.…”
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