AIMC Topic: Cross-Sectional Studies
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A calculator for musculoskeletal injuries prediction in surgeons: a machine learning approach.
Surgical endoscopy
Sep 16, 2024
BACKGROUND: Surgical specialists experience significant musculoskeletal strain as a consequence of their profession, a domain within the healthcare system often recognized for the pronounced impact of such issues. The aim of this study is to calculat...
Development and validation of machine learning models for predicting cancer-related fatigue in lymphoma survivors.
International journal of medical informatics
Sep 14, 2024
BACKGROUND: New cases of lymphoma are rising, and the symptom burden, like cancer-related fatigue (CRF), severely impacts the quality of life of lymphoma survivors. However, clinical diagnosis and treatment of CRF are inadequate and require enhanceme...
Development and validation of cardiometabolic risk predictive models based on LDL oxidation and candidate geromarkers from the MARK-AGE data.
Mechanisms of ageing and development
Sep 14, 2024
The predictive value of the susceptibility to oxidation of LDL particles (LDLox) in cardiometabolic risk assessment is incompletely understood. The main objective of the current study was to assess its relationship with other relevant biomarkers and ...
Diagnostic Performance of the Offline Medios Artificial Intelligence for Glaucoma Detection in a Rural Tele-Ophthalmology Setting.
Ophthalmology. Glaucoma
Sep 12, 2024
PURPOSE: This study assesses the diagnostic efficacy of offline Medios Artificial Intelligence (AI) glaucoma software in a primary eye care setting, using nonmydriatic fundus images from Remidio's Fundus-on-Phone (FOP NM-10). Artificial intelligence ...
Identifying Psychosocial and Ecological Determinants of Enthusiasm In Youth: Integrative Cross-Sectional Analysis Using Machine Learning.
JMIR public health and surveillance
Sep 12, 2024
BACKGROUND: Understanding the factors contributing to mental well-being in youth is a public health priority. Self-reported enthusiasm for the future may be a useful indicator of well-being and has been shown to forecast social and educational succes...
Machine learning algorithms to predict mild cognitive impairment in older adults in China: A cross-sectional study.
Journal of affective disorders
Sep 11, 2024
OBJECTIVE: This study aimed to explore the predictive value of machine learning (ML) in mild cognitive impairment (MCI) among older adults in China and to identify important factors causing MCI.
Evaluating text and visual diagnostic capabilities of large language models on questions related to the Breast Imaging Reporting and Data System Atlas 5 edition.
Diagnostic and interventional radiology (Ankara, Turkey)
Sep 9, 2024
PURPOSE: This study aimed to evaluate the performance of large language models (LLMs) and multimodal LLMs in interpreting the Breast Imaging Reporting and Data System (BI-RADS) categories and providing clinical management recommendations for breast r...
Analysis of anterior segment in primary angle closure suspect with deep learning models.
BMC medical informatics and decision making
Sep 9, 2024
OBJECTIVE: To analyze primary angle closure suspect (PACS) patients' anatomical characteristics of anterior chamber configuration, and to establish artificial intelligence (AI)-aided diagnostic system for PACS screening.
Machine learning approaches identify immunologic signatures of total and intact HIV DNA during long-term antiretroviral therapy.
eLife
Sep 9, 2024
Understanding the interplay between the HIV reservoir and the host immune system may yield insights into HIV persistence during antiretroviral therapy (ART) and inform strategies for a cure. Here, we applied machine learning (ML) approaches to cross-...
MyofAPPcial: Construct validity of a novel technological aid for improving clinical reasoning in the management of myofascial pain syndrome.
European journal of clinical investigation
Sep 6, 2024
BACKGROUND: Physiotherapists encounter challenges in diagnosing myofascial trigger points (MTrPs), which are crucial for managing myofascial pain but difficult due to their complex referred pain patterns. We aimed to assess if an interactive software...
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