Prediction and Screening of Lead-Free Double Perovskite Photovoltaic Materials Based on Machine Learning by Juan Wang, Yizhe Wang, Xiaoqin Liu, Xinzhong Wang

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Developing a novel aging assessment model to uncover heterogeneity in organ aging and screening of aging-related drugs by Yingqi Xu, Maohao Li, Congxue Hu, Yawen Luo, Xing Gao, Xinyu Li, Xia Li, Yunpeng Zhang

“…Furthermore, a random walk algorithm and a weighted integration approach combining gene set enrichment analysis were implemented to systematically screen potential drugs for mitigating multi-organ aging. …”
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Treatment decision algorithms for tuberculosis screening and diagnosis in children below 5 years hospitalised with severe acute malnutrition: a cost-effectiveness analysisResearch... by Marc d’Elbée, Nyashadzaishe Mafirakureva, Chishala Chabala, Minh Huyen Ton Nu Nguyet, Martin Harker, Clémentine Roucher, Gerald Businge, Perfect Shankalala, Bwendo Nduna, Veronica Mulenga, Maryline Bonnet, Eric Wobudeya, Olivier Marcy, Peter J. Dodd

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Post-processing methods for mitigating algorithmic bias in healthcare classification models: An extended umbrella review by Shaina Mackin, Vincent J. Major, Rumi Chunara, Remle Newton-Dame

“…Future research should empirically compare post-processing methods on binary classification models using real-world healthcare data. As commercial algorithms proliferate, health systems require proven, achievable strategies to maximize fairness.…”
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An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1. by Sergei L Kosakovsky Pond, David Posada, Eric Stawiski, Colombe Chappey, Art F Y Poon, Gareth Hughes, Esther Fearnhill, Mike B Gravenor, Andrew J Leigh Brown, Simon D W Frost

“…Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. …”
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Developing an Algorithm for Detecting Suspicious Trades in Tehran Stock Exchange Based on Spoof Trading Model by Reza Tehrani, Saeed Fallahpour, Hamid Nouralidokht

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A multi-algorithm prognostic model combining inflammatory indices and surgical features in distal cholangiocarcinoma by Yi Yin, Yi Yin, Luyuan Bai, Xinyue Mu, Xinyue Mu, Shan Zhang, Panpan Zhai, Panpan Zhai

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A neural network model enables worm tracking in challenging conditions and increases signal-to-noise ratio in phenotypic screens. by Weheliye H Weheliye, Javier Rodriguez, Luigi Feriani, Avelino Javer, Virginie Uhlmann, André E X Brown

“…Model-based tracking and deep learning approaches have addressed these issues to an extent, but there is still significant room for improvement in tracking crawling worms. …”
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Predictive model for determining the indications for automated 3D ultrasound for screening patients at low risk of developing breast tumors by A. E. Garanina, A. V. Kholin

“…To develop indications for 3D ultrasound based on predictive screening models for patients with a low risk of developing breast tumors based on the identification of the most significant risk factors.Patients and methods. …”
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Development and Validation of a Cost-Effective Machine Learning Model for Screening Potential Rheumatoid Arthritis in Primary Healthcare Clinics by Wu W, Hu X, Yan L, Li Z, Li B, Chen X, Lin Z, Zeng H, Li C, Mo Y, Wu Y, Wang Q

“…Using 10 classical machine learning algorithms, we developed screening models. Evaluation metrics determined the best model. …”
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Screening of multi deep learning-based de novo molecular generation models and their application for specific target molecular generation by Yishu Wang, Mengyao Guo, Xiaomin Chen, Dongmei Ai

“…Abstract Traditional virtual screening methods need to explore expanse and vast chemical spaces and need to be based on existing chemical libraries. …”
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Sensitive Multispectral Variable Screening Method and Yield Prediction Models for Sugarcane Based on Gray Relational Analysis and Correlation Analysis by Shimin Zhang, Huojuan Qin, Xiuhua Li, Muqing Zhang, Wei Yao, Xuegang Lyu, Hongtao Jiang

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Identification of maize kernel varieties based on interpretable ensemble algorithms by Chunguang Bi, Chunguang Bi, Xinhua Bi, Jinjing Liu, Hao Xie, Shuo Zhang, He Chen, Mohan Wang, Lei Shi, Lei Shi, Shaozhong Song

“…Morphological and hyperspectral data of maize samples were extracted and preprocessed, and three methods were used to screen features, respectively. The base learner of the Stacking integration model was selected using diversity and performance indices, with parameters optimized through a differential evolution algorithm incorporating multiple mutation strategies and dynamic adjustment of mutation factors and recombination rates. …”
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Development of prediction models for screening depression and anxiety using smartphone and wearable-based digital phenotyping: protocol for the Smartphone and Wearable Assessment f... by Sujin Kim, Ah Young Kim, Yu-Bin Shin, Seonmin Kim, Min-Sup Shin, Jinhwa Choi, Kyung Lyun Lee, Jisu Lee, Sangwon Byun, Heon-Jeong Lee, Chul-Hyun Cho

“…The Smartphone and Wearable Assessment for Real-Time Screening of Depression and Anxiety study aims to develop prediction algorithms to identify individuals at risk for depressive and anxiety disorders, as well as those with mild-to-severe levels of either condition or both. …”
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Development and Internal Validation of a Machine Learning-Based Colorectal Cancer Risk Prediction Model by Deborah Jael Herrera, Daiane Maria Seibert, Karen Feyen, Marlon van Loo, Guido Van Hal, Wessel van de Veerdonk

“…<b>Methods:</b> We analyzed data from 154,887 adults, aged 55–74 years, who participated in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. A risk prediction model was built using the Light Gradient Boosting Machine (LightGBM) algorithm. …”
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DKK3 and SERPINB5 as novel serum biomarkers for gastric cancer: facilitating the development of risk prediction models for gastric cancer by Yan-Yu Liu, Yan-Yu Liu, Yan-Fang Fu, Yan-Fang Fu, Wan-Yu Yang, Wan-Yu Yang, Zheng Li, Zheng Li, Qian Lu, Qian Lu, Xin Su, Xin Su, Jin Shi, Si-Qi Wu, Di Liang, Yu-Tong He, Yu-Tong He

“…The existing gastric cancer (GC) risk prediction models based on biomarkers are limited. This study aims to identify new promising biomarkers for GC to develop a risk prediction model for effective assessment, screening, and early diagnosis. …”
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The Bridge between Screening and Assessment: Establishment and Application of Online Screening Platform for Food Risk Substances by Kang Hu, Shaoming Jin, Hong Ding, Jin Cao

“…The screening comparison algorithm, the core of the screening model, is obtained through the improvement of the existing spectral library search algorithm. …”
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A recurrent neural network and parallel hidden Markov model algorithm to segment and detect heart murmurs in phonocardiograms. by Andrew McDonald, Mark J F Gales, Anurag Agarwal

“…These properties make the algorithm a promising tool for screening of abnormal heart murmurs.…”
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Revolutionizing pharmacology: AI-powered approaches in molecular modeling and ADMET prediction by Irfan Pathan, Arif Raza, Adarsh Sahu, Mohit Joshi, Yamini Sahu, Yash Patil, Mohammad Adnan Raza, Ajazuddin

“…It outlines the evolution of computational chemistry and the transformative role of AI in interpreting complex molecular data, automating feature extraction, and improving decision-making across the drug development pipeline. Core AI algorithms support vector machines, random forests, graph neural networks, and transformers are examined for their applications in molecular representation, virtual screening, and ADMET property prediction. …”
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RETRACTED ARTICLE: Screening and identification of susceptibility genes for cervical cancer via bioinformatics analysis and the construction of an mitophagy-related genes diagnosti... by Zhang Zhang, Fangfang Chen, Xiaoxiao Deng

“…Abstract Purpose This study aims to utilize bioinformatics methods to systematically screen and identify susceptibility genes for cervical cancer, as well as to construct and validate an mitophagy-related genes (MRGs) diagnostic model. …”
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