A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs by Fatemeh Salehi, Emmanuelle Salin, Benjamin Smarr, Sara Bayat, Arnd Kleyer, Georg Schett, Ruth Fritsch-Stork, Bjoern M. Eskofier

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Notice of Retraction: Molecular Diagnostic and Using Deep Learning Techniques for Predict Functional Recovery of Patients Treated of Cardiovascular Disease by Ar Junejo, Yin Shen, Asif Ali Laghari, Xiaobo Zhang, Hao Luo

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Machine learning based clinical decision tool to predict acute kidney injury and survival in therapeutic hypothermia treated neonates by Elif Keles, Syed Yaseen Ali, Pia Wintermark, Pieter Annaert, Floris Groenendaal, Suzan Şahin, Mehmet Yekta Öncel, Didem Armangil, Esin Koc, Malcolm R. Battin, Alistair J. Gunn, Adam Frymoyer, Valerie Chock, Djalila Mekahli, John van den Anker, Anne Smits, Karel Allegaert, Ulas Bagci

“…Our study aimed to utilize machine learning (ML) methods to predict the outcome of TH-treated NE neonates developing AKI and death during TH. …”
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A clinical data-driven machine learning approach for predicting the effectiveness of piperacillin-tazobactam in treating lower respiratory tract infections by Yemeng Yang, Kun Han, Jiatao Li, Tao Zhang, Zhijing Zhu, Ling Su, Zhaoyong Han, Chunyan Xu, Yi Lu, Likun Pan, Tao Yang

“…In the present study, we constructed a machine learning model based on patients’ clinical information to predict the clinical effectiveness of Piperacillin-tazobactam (TZP) (4:1) in treating bacterial lower respiratory tract infections (LRTIs), to assist clinicians in making better clinical decisions. …”
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Explainable machine learning model and nomogram for predicting the efficacy of Traditional Chinese Medicine in treating Long COVID: a retrospective study by Jisheng Zhang, Yang Chen, Aijun Zhang, Yi Yang, Liqian Ma, Hangqi Meng, Jintao Wu, Kean Zhu, Jiangsong Zhang, Ke Lin, Xianming Lin

“…This study aims to develop an explainable machine learning (ML) model and nomogram to identify Long COVID patients who may benefit from TCM, enhancing clinical decision-making.MethodsWe analyzed data from 1,331 Long COVID patients treated with TCM between December 2022 and February 2024 at three hospitals in Zhejiang, China. …”
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Using machine learning for mortality prediction and risk stratification in atezolizumab‐treated cancer patients: Integrative analysis of eight clinical trials by Yougen Wu, Wenyu Zhu, Jing Wang, Lvwen Liu, Wei Zhang, Yang Wang, Jindong Shi, Ju Xia, Yuting Gu, Qingqing Qian, Yang Hong

“…Our aim was to build a machine learning‐based risk stratification model for predicting mortality in atezolizumab‐treated cancer patients. …”
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Combination of ultrasound-based radiomics and deep learning with clinical data to predict response in breast cancer patients treated with neoadjuvant chemotherapy by Wu Tenghui, Liu Xinyi, Si Ziyi, Zhang Yanting, Ma Ziqian, Zhu Yiwen, Gan Ling

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Advancing patient care: Machine learning models for predicting grade 3+ toxicities in gynecologic cancer patients treated with HDR brachytherapy. by Andres Portocarrero-Bonifaz, Salman Syed, Maxwell Kassel, Grant W McKenzie, Vishwa M Shah, Bryce M Forry, Jeremy T Gaskins, Keith T Sowards, Thulasi Babitha Avula, Adrianna Masters, Jose G Schneider, Scott R Silva

“…<h4>Objective</h4>To develop and compare machine learning models for predicting grade 3 or higher toxicities in gynecological cancer patients treated with high dose rate (HDR) brachytherapy, aiming to contribute to personalized radiation treatments.…”
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Corrigendum to “Remote sensing and machine learning approach for zoning of wastewater drainage system” [Desalin Water Treat 319 (2024) 100549] by A. Saranya, Alanoud Al Mazroa, Mashael Maashi, T.M. Nithya, V. Priya

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Impact of large language models and vision deep learning models in predicting neoadjuvant rectal score for rectal cancer treated with neoadjuvant chemoradiation by Hyun Bin Kim, Hong Qi Tan, Wen Long Nei, Ying Cong Ryan Shea Tan, Yiyu Cai, Fuqiang Wang

“…Abstract This study aims to explore Deep Learning methods, namely Large Language Models (LLMs) and Computer Vision models to accurately predict neoadjuvant rectal (NAR) score for locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiation (NACRT). …”
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Using artificial neural networks to predict the compressive strength of cement and sawdust ash-treated lateritic soil by James Ukpai, Ugochukwu Okonkwo

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Advancing wastewater reuse: AI-driven insights into ozone-based organic pollutant reduction by Syed Muzzamil Hussain Shah, Sani I. Abba, Mohamed A. Yassin, Ebrahim Al-Qadami, Dahiru U. Lawal, Imtiaz Afzal Khan, Jamilu Usman, Haris U. Qureshi, Isam H. Aljundi

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Assessing the strength of lime-treated clayey soil reinforced with PET: A ML-based data-derived approach by Javadreza Vahedi, Mehdi Koohmishi

“…In this context, a machine learning (ML) model, i.e. XGBoost, is employed to delineate the most effective properties impacting the strength of clayey soil. …”
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Antiviral therapy can effectively suppress irAEs in HBV positive hepatocellular carcinoma treated with ICIs: validation based on multi machine learning by Shuxian Pan, Zibing Wang

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Understanding the determinants of treated bed net use in Ethiopia: A machine learning classification approach using PMA Ethiopia 2023 survey data. by Abraham Keffale Mengistu

“…Despite extensive distribution campaigns, 35% of insecticide-treated nets (ITNs) remain underutilized, hindering malaria control efforts. …”
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Longitudinal dynamic MRI radiomic models for early prediction of prognosis in locally advanced cervical cancer treated with concurrent chemoradiotherapy by Chang Cai, Ji-Feng Xiao, Rong Cai, Dan Ou, Yi-Wei Wang, Jia-Yi Chen, Hao-Ping Xu

“…Abstract Purpose To investigate the early predictive value of dynamic magnetic resonance imaging (MRI)-based radiomics for progression and prognosis in locally advanced cervical cancer (LACC) patients treated with concurrent chemoradiotherapy (CCRT). …”
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Discovery of a selective 5-HT2C agonist by generative machine learning using MegaSyn with applications to treating opioid use disorder by Thane Jones, Ph.D., Joshua S. Harris, Ph.D., Renuka Raman, Ph.D., Sean Ekins

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Development and validation of a prediction model for response to acupuncture in treating back pain using machine-learning: results from 2 independent clinical trials by Jiang-Ti Kong, Lu Tian, Rachel Manber, Sean Mackey

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Modeling the unconfined compressive strength of lateritic soil treated with FGD gypsum as a partial cement replacement by Chidananda M Linganagoudar, Shiva Kumar G, M S Ujwal, G Rohith, A Vinay, Poornachandra Pandit

“…To address these challenges, soil specimens were treated with varying cement contents (3%, 6%, 9%) and FGD gypsum additions (1%–6%). …”
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Decreased nitric oxide levels in the hippocampus may play a role in learning and memory deficits in ovariectomized rats treated by a high dose of estradiol by Reihaneh Sadeghian, Masoud Fereidoni, Mohammad Soukhtanloo, Hamid Azizi-Malekabadi, Mahmoud Hosseini

“…Sham-Est and OVX-Est Groups were treated with 4 mg/kg of estradiol valerate for 12 weeks. …”
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