Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

“…This study aims to develop artificial intelligence algorithms based on gait analysis, integrating sensor and computer vision (CV) data, to detect sarcopenia and CD. …”
Get full text

Predicting hepatocellular carcinoma outcomes and immune therapy response with ATP-dependent chromatin remodeling-related genes, highlighting MORF4L1 as a promising target by Chao Xu, Litao Liang, Guoqing Liu, Yanzhi Feng, Bin Xu, Deming Zhu, Wenbo Jia, Jinyi Wang, Wenhu Zhao, Xiangyu Ling, Yongping Zhou, Wenzhou Ding, Lianbao Kong

“…We utilized data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), applying machine learning algorithms to develop a prognostic model based on ACRRGs’ expression. …”
Get full text

Multi-atlas multi-modality morphometry analysis of the South Texas Alzheimer’s Disease Research Center postmortem repository by Nicolas Honnorat, Mariam Mojtabai, Karl Li, Jinqi Li, David Michael Martinez, Tanweer Rashid, Morgan Smith, Margaret E Flanagan, Elyas Fadaee, Morgan Fox Torres, Mallory Keating, Kevin Bieniek, Sudha Seshadri, Mohamad Habes

“…In general, our results establish that a combination of structural MRI sequences can provide enough informa- tion for state-of-the-art Deep Learning algorithms to almost perfectly separate brain tissues from a formalin buffered solution. …”
Get full text

Comparative evaluation of machine learning models versus TIMI score in ST-segment-elevation myocardial infarction patients by Mohit D. Gupta, Dixit Goyal, Shekhar Kunal, Manu Kumar Shetty, M.P. Girish, Vishal Batra, Ankit Bansal, Prashant Mishra, Mansavi Shukla, Vanshika Kohli, Akul Chadha, Arisha Fatima, Subrat Muduli, Anubha Gupta, Jamal Yusuf

“…Additionally, the performance of ML models both for in-hospital and 30-day outcomes was compared to that of TIMI score. …”
Get full text

Identification of novel molecular subtypes and construction of a prognostic signature via multi-omics analysis and machine learning in lung adenocarcinoma by Ke Ma, Jie Xu, Jie Xu, Congyue Wang, Congyue Wang, Xu Cao, Xu Cao, Wenjie Yu, Jingjing Xi, Xuan Zhang, Jiamin Zhan, Yang Liu, Aoyang Yu, Aoyang Yu, Shuhan Liu, Yanhua Liu, Yanhua Liu, Chong Chen, Chong Chen, Xiaoli Mai, Xiaoli Mai

“…The robustness of the model was assessed using the concordance index (C-index), Kaplan-Meier survival analyses, receiver operating characteristic (ROC) curves, and both univariate and multivariate Cox regression analyses. …”
Get full text

The prognostic and therapeutic significance of polyunsaturated fatty acid‐derived oxylipins in ST‐segment elevation myocardial infarction by Zhiyong Du, Yingyuan Lu, Ying Ma, Yunxiao Yang, Wei Luo, Sheng Liu, Ming Zhang, Yong Wang, Lei Li, Chun Li, Wei Wang, Hai Gao

“…Herein, we used targeted metabolomics and machine learning algorithms to develop an oxylipin‐based risk model to accurately predict recurrent major adverse cardiovascular events (MACE) after STEMI in two independent prospective cohorts with 2 years of follow‐up. …”
Get full text

Machine-Learning Parsimonious Prediction Model for Diagnostic Screening of Severe Hematological Adverse Events in Cancer Patients Treated with PD-1/PD-L1 Inhibitors: Retrospective... by Seok Jun Park, Seungwon Yang, Suhyun Lee, Sung Hwan Joo, Taemin Park, Dong Hyun Kim, Hyeonji Kim, Soyun Park, Jung-Tae Kim, Won Gun Kwack, Sung Wook Kang, Yun-Kyoung Song, Jae Myung Cha, Sang Youl Rhee, Eun Kyoung Chung

“…Among the tested ML algorithms, random forest achieved the highest accuracy (area under the receiver operating characteristic curve [AUROC] 0.88 for both cohorts). …”
Get full text

Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomization by Yuan Liu, Yuan Liu, Xin Yuan, Xin Yuan, Yu-Chan He, Yu-Chan He, Zhong-Hai Bi, Zhong-Hai Bi, Si-Yao Li, Si-Yao Li, Ye Li, Ye Li, Yan-Li Liu, Yan-Li Liu, Liu Miao, Liu Miao

“…Using LASSO regression, logistic regression, and RF analysis, both CRP and lymphocyte counts were consistently identified as risk factors for CAD, prior to and following PSM. …”
Get full text

Protocol and research program of the European registry and biobank for interstitial lung diseases (eurILDreg) by Ekaterina Krauss, Silke Tello, Jennifer Naumann, Sandra Wobisch, Clemens Ruppert, Stefan Kuhn, Poornima Mahavadi, Raphael W. Majeed, Philippe Bonniaud, Maria Molina-Molina, Athol Wells, Nik Hirani, Carlo Vancheri, Simon Walsh, Matthias Griese, Bruno Crestani, Andreas Guenther, on behalf of further eurILDreg investigators, RARE-ILD investigators

“…Abstract Background and Aims Interstitial lung diseases (ILDs), encompassing both pediatric and adult cases, present a diverse spectrum of chronic conditions with variable prognosis. …”
Get full text

Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinomaResearch in context by Bolin Song, Amaury Leroy, Kailin Yang, Tanmoy Dam, Xiangxue Wang, Himanshu Maurya, Tilak Pathak, Jonathan Lee, Sarah Stock, Xiao T. Li, Pingfu Fu, Cheng Lu, Paula Toro, Deborah J. Chute, Shlomo Koyfman, Nabil F. Saba, Mihir R. Patel, Anant Madabhushi

“…Pathology and radiology focused AI-based prognostic models have been independently developed for OPSCC, but their integration incorporating both primary tumour (PT) and metastatic cervical lymph node (LN) remains unexamined. …”
Get full text

Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench Testing by Marcio Luís Munhoz Amorim, Jorge Gomes Lima, Norah Nadia Sánchez Torres, Jose A. Afonso, Sérgio F. Lopes, João P. P. do Carmo, Lucas Vinicius Hartmann, Cicero Rocha Souto, Fabiano Salvadori, Oswaldo Hideo Ando Junior

“…This PoC system leverages open-source technology to provide a cost-effective and versatile solution for both research and practical applications. Initial laboratory tests validate its feasibility for real-time data acquisition and highlight its potential for creating datasets to support advanced diagnostic algorithms. …”
Get full text

Integrating ultrasound radiomics and clinicopathological features for machine learning-based survival prediction in patients with nonmetastatic triple-negative breast cancer by Wenwen, Zekun Jiang, Jingyan Liu, Dingbang Liu, Yiyue Li, Yushuang He, Haina Zhao, Lin Ma, Yixin Zhu, Qiongxian Long, Jun Gao, Honghao Luo, Heng Jiang, Kang Li, Xiaorong Zhong, Yulan Peng

“…A thorough chart review was conducted for each patient to collect clinicopathological and sonographic features, and ultrasound radiomics features were obtained by PyRadiomics. Deep learning algorithms were utilized to delineate ROIs on ultrasound images. …”
Get full text

Machine learning–guided single-cell multiomics uncovers GDF15-driven immunosuppressive niches in NSCLC: A translational framework for overcoming anti-PD-1 resistance by Xianfei Zhang, Zhengxin Yin, Xueyu Chen, Nengchong Zhang, Shengjia Yu, Congcong Zhu, Lianggang Zhu, Liulan Shao, Bin Li, Runsen Jin, Hecheng Li

“…Comparative evaluation of 22 survival algorithms across four NSCLC cohorts (n=156) led to the development of an Accelerated Oblique Random Survival Forest model, which outperformed conventional Cox regression and deep learning methods in predictive accuracy (training C-index=0.864; test C-index=0.748). …”
Get full text

An Underground Goaf Locating Framework Based on D-InSAR with Three Different Prior Geological Information Conditions by Kewei Zhang, Yunjia Wang, Feng Zhao, Zhanguo Ma, Guangqian Zou, Teng Wang, Nianbin Zhang, Wenqi Huo, Xinpeng Diao, Dawei Zhou, Zhongwei Shen

“…Furthermore, this investigation discusses the influence of deformation spatial resolution, the impacts of azimuth determination methodologies, and performance comparisons between non-hybrid and hybrid optimization algorithms. This study demonstrates that aligning the selection of deformation models with different types of prior geological information significantly improves the accuracy of underground goaf detection. …”
Get full text

Point-Of-Care low-field MRI in acute Stroke (POCS): protocol for a multicentric prospective open-label study evaluating diagnostic accuracy by Mauro Silvestrini, Simona Sacco, Massimo Caulo, Simona Marcheselli, Carmine Marini, Sergio Lucio Vinci, Angelo Galante, Marco Colasurdo, Raffaele Ornello, Matteo Foschi, Stefano Necozione, Mario Muselli, Paola Olimpia Achard, Luciano Fratocchi, Marco Cavallaro, Gabriele Polonara, Laura Straffi, Luca Sorrentino, Enrico Franconi, Marcello Alecci

“…Martino’ Polyclinic University Hospital. Both units will independently adjudicate the best treatment option, while the latter will provide historical HF-MRI data to develop artificial intelligence algorithms for LF-MRI images interpretation (Free University of Bozen-Bolzano). …”
Get full text

Preconception, prenatal and early childhood exposure to green space and risk of neurodevelopmental delays: a national cohort study among Medicaid enrollees by Hayon Michelle Choi, Krista F. Huybrechts, Sonia Hernandez-Diaz, Xinye Qiu, Michael Leung, Peter James, Matthew Shupler, Wanyu Huang, Yaguang Wei, Antonella Zanobetti, Christopher J McDougle, Joel Schwartz, Brent Coull, Marc Weisskopf, Stefania Papatheodorou

“…We examined exposure to green space during the preconception, prenatal, and postnatal periods to capture critical developmental windows both separately and with mutual adjustment. Neurodevelopmental outcomes were identified using validated algorithms and included autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), learning disabilities, speech and language disorders, coordination disorders, intellectual disabilities, and behavioral disorders. …”
Get full text

Development of a Predictive Model of Occult Cancer After a Venous Thromboembolism Event Using Machine Learning: The CLOVER Study by Anabel Franco-Moreno, Elena Madroñal-Cerezo, Cristina Lucía de Ancos-Aracil, Ana Isabel Farfán-Sedano, Nuria Muñoz-Rivas, José Bascuñana Morejón-Girón, José Manuel Ruiz-Giardín, Federico Álvarez-Rodríguez, Jesús Prada-Alonso, Yvonne Gala-García, Miguel Ángel Casado-Suela, Ana Bustamante-Fermosel, Nuria Alfaro-Fernández, Juan Torres-Macho

“…XGBoost, LightGBM, and CatBoost algorithms were used to train different prediction models, which were subsequently validated in a hold-out dataset. …”
Get full text

Associations of lung function impairment and biological aging with mortality and cardiovascular disease incidence: findings from UK biobank participants by Jiali Chen, Cheng Wang, Pengyu Duan, Yonghong Bi, Yao Meng, Weiyu Feng, Zhehao Jin, Hangbing Li, Huihui Wang, Xiaoyan Li, Kun Zuo, Xiangcheng Zhao, Longfei Li, Yuling Xing, Lan Luo, Yang Yu, Miao Yu, Muyan Cui, Bing Zhang

“…PhenoAgeAccel was calculated using algorithms based on clinical biomarkers, and frailty was evaluated according to five established criteria. …”
Get full text

Estimation of the water content of needles under stress by Erannis jacobsoni Djak. via Sentinel-2 satellite remote sensing by Jiaze Guo, Xiaojun Huang, Xiaojun Huang, Xiaojun Huang, Debao Zhou, Junsheng Zhang, Gang Bao, Gang Bao, Siqin Tong, Siqin Tong, Yuhai Bao, Yuhai Bao, Dashzebeg Ganbat, Dorjsuren Altanchimeg, Davaadorj Enkhnasan, Mungunkhuyag Ariunaa

“…Needle leaf water content exhibits a clear response to these changes and is highly sensitive in reflecting the degree of tree damage.MethodsIn this work, we combine vegetation indices with machine learning algorithms to estimate the water content of needles at a large scale. …”
Get full text

Population-based colorectal cancer risk prediction using a SHAP-enhanced LightGBM model by Guinian Du, Hui Lv, Yishan Liang, Jingyue Zhang, Qiaoling Huang, Guiming Xie, Xian Wu, Hao Zeng, Lijuan Wu, Jianbo Ye, Wentan Xie, Xia Li, Yifan Sun

“…Seven ML algorithms were systematically compared, with Light Gradient Boosting Machine (LightGBM) ultimately selected as the optimal framework. …”
Get full text