A portable retina fundus photos dataset for clinical, demographic, and diabetic retinopathy prediction by Chenwei Wu, David Restrepo, Luis Filipe Nakayama, Lucas Zago Ribeiro, Zitao Shuai, Nathan Santos Barboza, Maria Luiza Vieira Sousa, Raul Dias Fitterman, Alexandre Durao Alves Pereira, Caio Vinicius Saito Regatieri, Jose Augusto Stuchi, Fernando Korn Malerbi, Rafael E. Andrade

“…The mBRSET dataset serves as a resource for developing AI algorithms and investigating real-world applications, enhancing ophthalmological care in resource-constrained environments.…”
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Quality of care for severe acute malnutrition delivered by community health workers in southern Bangladesh by Chloe Puett, Jennifer Coates, Harold Alderman, Kate Sadler

“…CHWs screened children at community level using a mid‐upper arm circumference measurement, and treated cases without medical complications. …”
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Identification of Ferroptosis‐Related Gene in Age‐Related Macular Degeneration Using Machine Learning by Meijiang Zhu, Jing Yu

“…Differentially expressed genes (DEGs) were selected and intersected with genes from the ferroptosis database to obtain differentially expressed ferroptosis‐associated genes (DEFGs). Machine learning algorithms were employed to screen diagnostic genes. …”
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The Growing Impact of Natural Language Processing in Healthcare and Public Health by Aadit Jerfy, Owen Selden, Rajesh Balkrishnan PhD

“…Automating labor intensive and tedious tasks with language processing algorithms, using text analytics systems and machine learning to analyze social media data and extracting insights from unstructured data allows for better public sentiment analysis, enhancement of risk prediction models, improved patient communication, and informed treatment decisions. …”
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Protecting kidney function: from mechanisms to therapeutic targets and traditional Chinese medicine by Yilin Meng, Lu Sui, Ligeer Che, Zihang Jin, Yutong Ma, Li Sun

“…Adaptive design and using human kidney organoid models for drug screening can determine the active ingredients efficiently. …”
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Design and validation of a novel multiple sites signal acquisition and analysis system based on pressure stimulation for human cardiovascular information by Gaiqin Liu, Yuan Li, Longcong Chen, Juan Jiang, Jie Tian, Panpan Feng

“…Furthermore, the results suggest that the system can facilitate in-depth research into the relationships between collected signals and CVDs, provide rich raw data for cardiovascular health assessment and disease prediction models based on machine learning algorithms, and offer a new non-invasive method for early diagnosis, evaluation, and prediction of CVDs.…”
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Mechanism and relevance of necroptosis to immune microenvironment of periodontitis: A pilot study by ZHENG Zhanglong, LI Jia, JIANG Jirui, SHAN Zhengnan, LI Shengjiao

“…[Objective:] To explore the effect and mechanism of necroptosis on the immune microenvironment of periodontitis. [Methods:] We screened out the differentially expressed necroptosis-related genes in periodontitis, first calculated the hub genes through machine learning algorithms, and constructed a diagnostic model. …”
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Advancing clinical biochemistry: addressing gaps and driving future innovations by Haiou Cao, Enwa Felix Oghenemaro, Amaliya Latypova, Amaliya Latypova, Munthar Kadhim Abosaoda, Munthar Kadhim Abosaoda, Munthar Kadhim Abosaoda, Gaffar Sarwar Zaman, Anita Devi

“…However, concerns regarding algorithmic bias, data privacy, lack of transparency in decision-making (“black box” models), and over-reliance on automated systems pose significant challenges that must be addressed for responsible AI integration. …”
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RNA m7G methylation regulators and targets significantly contribute to chronic obstructive pulmonary disease by Chenyu Zhu, Luyi Tan, Xinyu Zhang, Wenli Cheng, Min Li, Yibo Chen, Wenjuan Zhang

“…In this study, the combined roles of m7G methylation regulators were explored in COPD for the first time by integrated bioinformatic methods. The machine algorithms screened 7 disease signature genes relevant to clinical indicators, including CYFIP2, EIF3D, EIF4G3, GEMIN5, METTL1, SNUPN and NCBP2, and METTL1 was related to the progression in COPD. …”
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Epidemiological and pharmacoeconomic aspects of HIV infection in military by Yu. I. Bulankov, M. A. Bulygin, A. V. Bespalov, K. V. Zhdanov, A. A. Murachev, K. S. Ivanov, Yu. I. Lyashenko

“…The research compares two competitive models: “Current Situation” - without the introduction of algorithms for early detection and treatment of HIV infection, and “Prognosis” - with the introduction of these algorithms.The following results are obtained: implementing a mandatory triennial screening for HIV-antibodies among military personnel allows to raise the detection of HIV-positive military personnel in the early stages of the disease by 55%. …”
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Мethods of Machine Learning in Ophthalmology: Review by D. D. Garri, S. V. Saakyan, I. P. Khoroshilova-Maslova, A. Yu. Tsygankov, O. I. Nikitin, G. Yu. Tarasov

“…Machine learning includes models and algorithms that mimic the architecture of biological neural networks. …”
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Identification of M2 macrophage-related genes associated with diffuse large B-cell lymphoma via bioinformatics and machine learning approaches by Jiayi Zhang, Zhixiang Jia, Jiahui Zhang, Xiaohui Mu, Limei Ai

“…Using the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine Recursive Feature Elimination (SVM-RFE), and Random Forest (RF) algorithms, we screened for seven potential diagnostic biomarkers with strong diagnostic capabilities: SMAD3, IL7R, IL18, FAS, CD5, CCR7, and CSF1R. …”
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Integrating equity, diversity, and inclusion throughout the lifecycle of artificial intelligence for healthcare: a scoping review. by Ting Wang, Elham Emami, Dana Jafarpour, Raymond Tolentino, Genevieve Gore, Samira Abbasgholizadeh Rahimi

“…Previous research has shown that AI models improve when socio-demographic factors such as gender and race are considered. …”
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Identification of novel gut microbiota-related biomarkers in cerebral hemorrhagic stroke by Fengli Ye, Huili Li, Hongying Li, Xiue Mu

“…Functional enrichment, gene set enrichment analysis (GSEA), and protein–protein interaction (PPI) analyses were performed. Hub genes were screened using LASSO, RandomForest, and SVM-RFE algorithms. …”
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Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics. by Wenlong Kuang, Jianwu Huang, Yulu Yang, Yuhua Liao, Zihua Zhou, Qian Liu, Hailang Wu

“…The 10 MI-related hub MitoDEGs were then obtained by eight different algorithms. Immunoassays showed a significant increase in monocyte macrophage and T cell infiltration. …”
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Role of Artificial Intelligence and Personalized Medicine in Enhancing HIV Management and Treatment Outcomes by Ashok Kumar Sah, Rabab H. Elshaikh, Manar G. Shalabi, Anass M. Abbas, Pranav Kumar Prabhakar, Asaad M. A. Babker, Ranjay Kumar Choudhary, Vikash Gaur, Ajab Singh Choudhary, Shagun Agarwal

“…Despite these innovations, challenges such as data privacy, algorithmic bias, and the need for clinical validation remain. …”
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The two ends of the spectrum: comparing chronic schizophrenia and premorbid latent schizotypy by actigraphy by Szandra László, Ádám Nagy, József Dombi, Emőke Adrienn Hompoth, Emese Rudics, Zoltán Szabó, András Dér, András Búzás, Zsolt János Viharos, Anh Tuan Hoang, Vilmos Bilicki, István Szendi

“…By applying model-explaining tools to the well-performing models, we could conclude the movement patterns and characteristics of the groups. …”
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Collaborative Filtering Techniques for Predicting Web Service QoS Values in Static and Dynamic Environments: A Systematic and Thorough Analysis by Ghizlane Khababa, Sadik Bessou, Fateh Seghir, Nor Hazlyna Harun, Abdulaziz S. Almazyad, Pradeep Jangir, Ali Wagdy Mohamed

“…Key insights were gathered on algorithms, evaluation metrics, datasets, and performance outcomes, with a focus on CF methods and advancements in hybrid and context-aware models. …”
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Deciphering the role of cuproptosis in the development of intimal hyperplasia in rat carotid arteries using single cell analysis and machine learning techniques by Miao He, Hui Chen, Zhengli Liu, Boxiang Zhao, Xu He, Qiujin Mao, Jianping Gu, Jie Kong

“…Methods: We downloaded single-cell sequencing and bulk transcriptome data from the GEO database to screen for copper-growth-associated genes (CAGs) using machine-learning algorithms, including Random Forest and Support Vector Machine. …”
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Advancing Mn-based electrocatalysts: Evolving from Mn-centered octahedral entities to bulk forms by Huan Li, Jinchao Xu, Liyuan Yang, Wanying Wang, Bin Shao, Fangyi Cheng, Chunning Zhao, Weichao Wang

“…According to the catalytic requirements of an individual entity and its stacking modes, we further developed a search algorithm to identify three-dimensional (3D) structures from 154,718 candidates, pinpointing CaMnO3 as the most effective one among the screened candidates. …”
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