AIMC Topic: Machine Learning
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The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review.
JMIR medical informatics
Jun 19, 2025
BACKGROUND: Machine learning (ML) and big data analytics are rapidly transforming health care, particularly disease prediction, management, and personalized care. With the increasing availability of real-world data (RWD) from diverse sources, such as...
Predicting Early-Onset Colorectal Cancer in Individuals Below Screening Age Using Machine Learning and Real-World Data: Case Control Study.
JMIR cancer
Jun 19, 2025
BACKGROUND: Colorectal cancer is now the leading cause of cancer-related deaths among young Americans. Accurate early prediction and a thorough understanding of the risk factors for early-onset colorectal cancer (EOCRC) are vital for effective preven...
Sentiment Analysis Using a Large Language Model-Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation.
JMIR infodemiology
Jun 19, 2025
BACKGROUND: The opioid crisis poses a significant health challenge in the United States, with increasing overdoses and death rates due to opioids mixed with other illicit substances. Various strategies have been developed by federal and local governm...
WISP2/CCN5 revealed as a potential diagnostic biomarker for endometriosis based on machine learning and single-cell transcriptomic analysis.
Functional & integrative genomics
Jun 19, 2025
OBJECTIVE: Endometriosis is a prevalent gynecological disease characterized by the ectopic growth of functional endometrial tissue outside the uterine cavity, affecting millions of women worldwide. Currently, the definitive diagnosis relies on invasi...
An In-depth overview of artificial intelligence (AI) tool utilization across diverse phases of organ transplantation.
Journal of translational medicine
Jun 18, 2025
Artificial Intelligence (AI) offers a revolutionary approach to improve decision-making in medicine through the use of advanced computational tools. Its ability to analyze large and complex datasets enables a thorough evaluation of multiple factors, ...
Machine learning model for predicting recurrence following intensity-modulated radiation therapy in nasopharyngeal carcinoma.
World journal of surgical oncology
Jun 18, 2025
BACKGROUND: Nasopharyngeal carcinoma (NPC) exhibits unique histopathological characteristics compared to other head and neck cancers. The prognosis of NPC patients after intensity-modulated radiation therapy (IMRT) has not been fully studied, and the...
Development of Machine Learning-Based Risk Prediction Models to Predict Rapid Weight Gain in Infants: Analysis of Seven Cohorts.
JMIR public health and surveillance
Jun 18, 2025
BACKGROUND: Rapid weight gain (RWG) during infancy, defined as an upward crossing of one centile line on a weight growth chart, is highly predictive of subsequent obesity risk. Identification of infant RWG could facilitate obesity risk assessment fro...
A multi-gene predictive model for the radiation sensitivity of nasopharyngeal carcinoma based on machine learning.
eLife
Jun 18, 2025
Radiotherapy resistance in nasopharyngeal carcinoma (NPC) is a major cause of recurrence and metastasis. Identifying radiotherapy-related biomarkers is crucial for improving patient survival outcomes. This study developed the nasopharyngeal carcinoma...
Chemical imaging for biological systems: techniques, AI-driven processing, and applications.
Journal of materials chemistry. B
Jun 18, 2025
Visualizing the chemical compositions of biological samples is pivotal to advancing biological sciences, with the past two decades witnessing the emergence of innovative chemical imaging platforms such as single-molecule imaging, coherent Raman scatt...
A Machine Learning-Based Clustering Analysis to Explore Bisphenol A and Phthalate Exposure from Medical Devices in Infants with Congenital Heart Defects.
Environmental health perspectives
Jun 18, 2025
BACKGROUND: Plastic-containing medical devices are commonly used in critical care units and other patient care settings. Patients are often exposed to xenobiotic agents that are leached out from plastic-containing medical devices, including bisphenol...
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