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

“…A clinically implementable web-based risk calculator was successfully developed for real-time probability estimation.ConclusionsOur LightGBM-based model achieves high predictive accuracy while maintaining clinical interpretability, effectively bridging the gap between complex ML systems and practical clinical decision-making. …”
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The Clinical Significance of Abnormal Electroencephalography (EEG) Patterns in Patients with Neuropsychiatric Disorders Due to Anti-NMDA Receptor Encephalitis: A Comparative Study by Alvaro Moreno-Avellán, Arely Juarez-Jaramillo, Maria del Carmen Fernandez Gonzalez-Aragon, Gerardo Quiñones-Pesqueira, Luz Maria Pineda-Centeno, Mariana Espinola-Nadurille, Victoria Martinez-Angeles, Francisco Martinez-Carrillo, Veronica Rivas-Alonso, Daniel San-Juan, Jose Flores-Rivera, Jesus Ramirez-Bermudez

“…These findings support the integration of EEG into diagnostic algorithms to guide early detection and management of autoimmune encephalitis.…”
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Opportunistic Diagnostics of Dental Implants in Routine Clinical Photon-Counting CT Acquisitions by Maurice Ruetters, Holger Gehrig, Christian Mertens, Sinan Sen, Ti-Sun Kim, Heinz-Peter Schlemmer, Christian H. Ziener, Stefan Schoenberg, Matthias Froelich, Marc Kachelrieß, Stefan Sawall

“…This is the first in vivo study demonstrating the feasibility of opportunistic dental diagnostics using PCCT in a clinical setting. While MAR reduces peripheral artifacts, it adversely affects image clarity near implants. …”
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Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer by Dong Pan, Dong Pan, Dong Pan, Cheng-Yan Zhang, Cheng-Yan Zhang, Cheng-Yan Zhang, Ya-Fei Wang, Ya-Fei Wang, Shuang Liu, Shuang Liu, Shuang Liu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu

“…GSEA revealed that high STAT3 expression enhanced epithelial apoptosis and TNF-α/NFκB signaling while suppressing pro-tumorigenic pathways, which was associated with an immunosuppressive microenvironment, whereas low STAT3 correlated with T-cell exhaustion. …”
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Use of a convolutional neural network for direct detection of acid-fast bacilli from clinical specimens by Paul English, Muir J. Morrison, Blaine Mathison, Elizabeth Enrico, Ryan Shean, Brendan O'Fallon, Deven Rupp, Katie Knight, Alexandra Rangel, Jeffrey Gilivary, Amanda Vance, Haleina Hatch, Leo Lin, David P. Ng, Salika M. Shakir

“…By building on our work, researchers can develop better algorithms to improve the diagnosis of AFB, reducing the burden on laboratory staff and improving diagnostic speed and accuracy of these medically important organisms.…”
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Advanced classification of optical water types and ensemble learning models for Chl-a inversion in Dongting and Poyang lakes using Sentinel-2 remote sensing: assessing the impact o... by Kai Xiong, Bin Deng, Jiang Liu, Zhixin Guan, Weizhi Lu, Changbo Jiang, Wei Luo, Han Rao, Longbin Yin, Kang Yang

“…Further analysis indicated that OWT2 in Dongting Lake is prone to algal blooms, while OWT3 and OWT4 are dominated by non-algal particles. …”
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Artificial intelligence-based prediction of second stage duration in labor: a multicenter retrospective cohort analysisResearch in context by Xiaoqing Huang, Xiaodan Di, Suiwen Lin, Minrong Yao, Suijin Zheng, Shuyi Liu, Wayan Lau, Zhixin Ye, Zilian Wang, Bin Liu

“…Summary: Background: Duration of second stage of labor is crucial for fetal delivery, but the optimal length of this stage remains controversial. While extending the duration of second stage can reduce primary cesarean delivery rates, it may increase maternal and neonatal morbidities as the duration progresses. …”
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Identifying low-risk breast cancer patients for axillary biopsy exemption: a multimodal preoperative predictive model by Jiaqi Zhang, Jianing Zhang, Zhihao Liu, Yudong Zhou, Xiaoni Zhao, Yalong Wang, Danni Li, Jinsui Du, Chenglong Duan, Yi Pan, Qi Tian, Feiqian Wang, Ke Wang, Lizhe Zhu, Bin Wang

“…Abstract Background As the most prevalent female malignancy worldwide, breast cancer frequently involves axillary lymph node metastasis (ALNM), which critically affects therapeutic algorithms. Current guidelines mandate preoperative ultrasound-guided axillary biopsy for suspicious lymph nodes, potentially exposing some low-risk patients with negative results to invasive risks. …”
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A photogrammetric approach to the estimation of distance to animals in camera trap images by B. Mirka, C.D. Lippitt, G.M. Harris, R. Converse, M. Gurule, S.E. Sesnie, M.J. Butler, D.R. Stewart, Z. Rossman

“…These methods have the potential, when paired with deep learning algorithms or crowdsourcing, to automate the process of wildlife identification and distance estimation, reducing the need for manual fieldwork or analysis while increasing the precision and replicability of population estimates. …”
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GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women by Li Yi, Jaime E. Hart, Grete Wilt, Cindy R. Hu, Marcia Pescador Jimenez, Pi-I Debby Lin, Esra Suel, Perry Hystad, Steve Hankey, Wenwen Zhang, Jorge E. Chavarro, Francine Laden, Peter James

“…Street-view greenspace (%trees, %grass, %other greenspace [flowers/plants/fields]) were derived from 2019 street-view imagery using deep-learning algorithms at a 100-meter resolution and linked to 10-minute GPS observations. …”
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Predictive model for sarcopenia in chronic kidney disease: a nomogram and machine learning approach using CHARLS data by Renjie Lu, Shiyun Wang, Pinghua Chen, Fangfang Li, Fangfang Li, Pan Li, Qian Chen, Xuefei Li, Fangyu Li, Suxia Guo, Jinlin Zhang, Jinlin Zhang, Dan Liu, Zhijun Hu

“…Model accuracy was evaluated using calibration curves, while predictive performance was assessed through receiver operating characteristic (ROC) and decision curve analysis (DCA). …”
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Efficacy and safety of ruxolitinib combined with steroids for first-line treatment of acute graft-versus-host disease after hematopoietic stem cell transplantation: a single-center... by Yan Yang, Yuan Huo, Dong Zhou, Zhijie Kang, Yanan Huang, Ying Wang, Guangjun Fan, Liyuan Ma, Jinsong Yan, Jinsong Yan, Jinsong Yan

“…Steroids are the standard first-line treatment for acute GVHD (aGVHD); however, standardized treatment algorithms for patients who do not respond to steroid therapy are lacking. …”
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Construction of a risk prediction model for occupational noise-induced hearing loss using routine blood and biochemical indicators in Shenzhen, China: a predictive modelling study by Wenting Feng, Wen Zhang, Yan Guo, Naixing Zhang, Liang Zhou, Dafeng Lin, Linlin Chen, Caiping Li, Liuwei Shi, Xiangli Yang, Peimao Li, Dianpeng Wang

“…Routine blood and biochemical indicators were extracted from the case data, and a range of machine learning algorithms including extreme gradient boosting (XGBoost) were employed to construct predictive models. …”
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Design and Implementation of a Deep Learning-Based Hand Gesture Recognition System for Rehabilitation Internet-of-Things (RIoT) Environments Using MediaPipe by Nurul Hanis Mohd Dhuzuki, Ahmad Anwar Zainuddin, Nur Anis Sofea Kamarul Zaman, Alin Nur Maisarah Ahmad Razmi, Wonderful Shammah Kaitane, Asmarani Ahmad Puzi, Mohd Naqiuddin Johar, Maslina Yazid, Nor Azlin Mohd Nordin, Shahrul Naim Sidek, Hasan Firdaus Mohd Zaki

“…The methodology involves the integration of MediaPipe for detecting hand landmarks and adaptive sensitivity algorithms to ensure reliable recognition across different environments, such as varying lighting and hand positions. …”
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Development and validation of a machine learning-based risk prediction model for stroke-associated pneumonia in older adult hemorrhagic stroke by Yi Cao, Yi Cao, Haipeng Deng, Shaoyun Liu, Xi Zeng, Yangyang Gou, Weiting Zhang, Yixinyuan Li, Hua Yang, Min Peng

“…Model performance was compared using Delong's test or Bootstrap test, while sensitivity, specificity, accuracy, precision, recall, and F1-score evaluated predictive efficacy. …”
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Three-Year On-Orbit Radiometric Performance of the SDGSAT-1 Multispectral Imager (MSI) by Lin Yan, Enchuan Qiao, Changyong Dou, Hao Zhang, Zhenzhen Cui, Yonghong Hu, Xiao-Ming Li, Jinlong Ai

“…Further efforts including enhanced calibration algorithms developing, cross radiometric calibration with payloads have good radiometric performance will be conducted. …”
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An IoT-enabled AI system for real-time crop prediction using soil and weather data in precision agriculture by MD Shaifullah Sharafat, Nilavro Das Kabya, Rahimul Islam Emu, Mehrab Uddin Ahmed, Jakaria Chowdhury Onik, Mohammad Aminul Islam, Riasat Khan

“…Several machine learning algorithms, including Random Forest, Gradient Boosting, and Stacking ensembles, as well as deep learning models such as TabNet, were evaluated for crop prediction. …”
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Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing by Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya Daanii Rachmanto, Affan Ardana, In Kee Kim

“…We compare various KD algorithms to identify the technique that produces a smaller model with the modest accuracy drop. …”
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A systematic comparison of short-term and long-term mortality prediction in acute myocardial infarction using machine learning models by Yawei Yang, Junjie Tang, Liping Ma, Feng Wu, Xiaoqing Guan

“…CBC parameters and renal biomarkers were pivotal in short-term models, while therapeutic interventions gained prominence over time. …”
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Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning by Oriyomi Raheem, Misael M. Morales, Wen Pan, Carlos Torres-Verdín

“…One of the main challenges in characterizing pore structure is how to use data from core plugs to establish a relationship with microscopic pore and throat properties, enabling more accurate predictions of capillary pressure. While special core analysis laboratory experiments are effective, they are time-consuming and expensive. …”
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