Building a Human Digital Twin (HDTwin) Using Large Language Models for Cognitive Diagnosis: Algorithm Development and Validation by Gina Sprint, Maureen Schmitter-Edgecombe, Diane Cook

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Palmitoylation-related gene ZDHHC22 as a potential diagnostic and immunomodulatory target in Alzheimer’s disease: insights from machine learning analyses and WGCNA by Sanying Mao, Xiyao Zhao, Lei Wang, Yilong Man, Kaiyuan Li

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Penentuan Jalur Diagnostik Penyakit Berbasis Konsep Pembelajaran Mesin: Studi kasus Penyakit Hepatitis C by Jimmy Tjen, Valentino Pratama

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Predicting radiation pneumonitis in lung cancer using machine learning and multimodal features: a systematic review and meta-analysis of diagnostic accuracy by Zhi Chen, GuangMing Yi, XinYan Li, Bo Yi, XiaoHui Bao, Yin Zhang, XiaoYue Zhang, ZhenZhou Yang, Zhengjun Guo

“…By selecting multiple machine learning algorithm frameworks and competing for the best combination model based on research goals, the reliability and accuracy of the radiation pneumonitis prediction model can be greatly improved. …”
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Modified Diagnostic Criteria Tools for Familial Hypercholesterolemia without the Requirement for Clinical Genetic Testing: Rationale and Design of the MOOCS Adaptive Clinical Trial by Satyanarayana Upadhyayula

“…Various available FH diagnostic tools are grouped together in the FH diagnostic criteria tool universal algorithm. …”
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A Clinical Validation of a Diagnostic Test for Esophageal Adenocarcinoma Based on a Novel Serum Glycoprotein Biomarker Panel: PromarkerEso by Jordana Sheahan, Iris Wang, Peter Galettis, David I. Watson, Virendra Joshi, Michelle M. Hill, Richard Lipscombe, Kirsten Peters, Scott Bringans

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Adoption of Compound Echocardiography under Artificial Intelligence Algorithm in Fetal Congenial Heart Disease Screening during Gestation by Guowei Han, Tianliang Jin, Li Zhang, Chen Guo, Hua Gui, Risu Na, Xuesong Wang, Haihua Bai

“…This research was aimed at exploring the diagnostic and screening effect of composite echocardiography based on the artificial intelligence (AI) segmentation algorithm on fetal congenital heart disease (CHD) during pregnancy, so as to reduce the birth rate of newborns with CHD. …”
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Data Assimilation Informed Model Structure Improvement (DAISI) for Robust Prediction Under Climate Change: Application to 201 Catchments in Southeastern Australia by Julien Lerat, Francis Chiew, David Robertson, Vazken Andréassian, Hongxing Zheng

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Efficacy of two radiographic algorithms for detection of peri-implant bone defects on cone-beam computed tomography scans by Faezeh Yousefi, Ali Heidari, Azita Ehsani, Maryam Farhadian, Marzieh Ehsani

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Identification of Biomarkers Associated with Heart Failure Caused by Idiopathic Dilated Cardiomyopathy Using WGCNA and Machine Learning Algorithms by Mengyi Sun, Linping Li

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Discovering sequential patterns and interrelations among multiple diseases in electronic medical records using cSPADE algorithm by He Ma, Qianxin Huang, Hong Zhang, Hui Song, Bo Zhang, Ying Liu, Lin Zhang

“…Conclusion Our findings demonstrate the effectiveness of the constrained SPADE (cSPADE) algorithm in comorbidity research and highlight several clinically significant sequential comorbidity patterns. …”
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A Novel Diagnostic Framework with an Optimized Ensemble of Vision Transformers and Convolutional Neural Networks for Enhanced Alzheimer’s Disease Detection in Medical Imaging by Joy Chakra Bortty, Gouri Shankar Chakraborty, Inshad Rahman Noman, Salil Batra, Joy Das, Kanchon Kumar Bishnu, Md Tanvir Rahman Tarafder, Araf Islam

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Identifying candidate biomarkers for detecting bronchogenic carcinoma stages using metaheuristic algorithms based on information fusion theory by Bagher Khalvati, Kaveh Kavousi, Amir Hosein Keyhanipour, Masoud Arabfard

“…To identify robust biomarkers, we applied eight metaheuristic algorithms for feature selection, combined with four classification methods and two data fusion techniques to optimize performance. …”
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Integrating Clinical and Transcriptomic Profiles Associated with Vitamin D to Enhance Disease-Free Survival in Cervical Cancer Recurrence Using the CatBoost Algorithm by Geeitha Senthilkumar, Renuka Pitchaimuthu, Seshathiri Dhanasekaran, Prabu Sankar Panneerselvam

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ML-based approach to potato diseases diagnosis using image processing and whale optimization algorithm for feature selection by Zhongxu Li, Seyed Mohamad Javidan

“…A significant challenge in this area is the design and implementation of algorithms capable of handling large datasets efficiently, reducing diagnostic time, and enhancing diagnostic accuracy. …”
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Advancements in Circulating Tumor Cell Detection for Early Cancer Diagnosis: An Integration of Machine Learning Algorithms with Microfluidic Technologies by Ling An, Yi Liu, Yaling Liu

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Federated Learning Based on an Internet of Medical Things Framework for a Secure Brain Tumor Diagnostic System: A Capsule Networks Application by Roman Rodriguez-Aguilar, Jose-Antonio Marmolejo-Saucedo, Utku Köse

“…This research introduces an analytical intelligence system based on an Internet of Medical Things (IoMT) framework that employs federated learning to provide a safe and effective diagnostic solution for brain tumor identification. …”
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Integrating machine learning and genetic evidence to uncover novel gene biomarkers for colorectal cancer diagnosis by Li Zhou, Lihua Yu, Mingjing Liao, Tingting Peng, Leilei Zhang, Chengyun Han, Yuan Li, Jiwang Zhang

“…Notably, the glmBoost + RF algorithm identified an eight-gene diagnostic model with high precision, pinpointing key genes such as CLDN1, IFITM1, and FOXQ1, which exhibited strong diagnostic performance (AUC > 0.9). …”
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Rapid diagnosis of power battery faults in new energy vehicles based on improved boosting algorithm and big data by Jiali Wang, Jia Chen

“…Subsequently, the importance of indicators in the data was analyzed using the Random Forest algorithm (RF). Finally, three improved Boosting algorithms were proposed, namely Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting Tree (XGBoost), and Gradient Boosting Decision Tree (CatBoost). …”
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Intelligent brain tumor detection using hybrid finetuned deep transfer features and ensemble machine learning algorithms by Rakesh Salakapuri, Panduranga Vital Terlapu, Kishore Raju Kalidindi, Ramesh Naidu Balaka, D. Jayaram, T. Ravikumar

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