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Using machine learning to predict patients with polycystic ovary disease in Chinese women.
Taiwan J Obstet Gynecol
January 2025
Graduate Institute of Applied Science and Engineering, Fu Jen Catholic University, New Taipei City, Taiwan. Electronic address:
Objective: With an estimated global frequency ranging from5 % to 21 %, polycystic ovary syndrome (PCOS) is one of the most prevalent hormonal disorders. There are many factors found to be related to PCOS. However, most of these researches used traditional methods such as multiple logistic regression (LR).
View Article and Find Full Text PDFDeveloping a fully applicable machine learning (ML) based sex classification model using linear cranial dimensions.
Sci Rep
December 2024
University Department of Forensic Sciences, University of Split, Split, Croatia.
Recent advances in artificial intelligence (AI) and machine learning (ML) applications have elevated accomplishments in various scientific fields, primarily those that benefit the economy and society. Contemporary threats, such as armed conflicts, natural and man-made disasters, and illegal immigration, often require fast and innovative but reliable identification aids, in which forensic anthropology has a significant role. However, forensic anthropology has not yet exploited new scientific advances but instead relies on traditionally used methods.
View Article and Find Full Text PDFRadiomics-driven spectral profiling of six kidney stone types with monoenergetic CT reconstructions in photon-counting CT.
Eur Radiol
December 2024
Department of Diagnostic and Interventional Radiology, Federal Armed Services Hospital Koblenz, Koblenz, Germany.
Objectives: Urolithiasis, a common and painful urological condition, is influenced by factors such as lifestyle, genetics, and medication. Differentiating between different types of kidney stones is crucial for personalized therapy. The purpose of this study is to investigate the use of photon-counting computed tomography (PCCT) in combination with radiomics and machine learning to develop a method for automated and detailed characterization of kidney stones.
View Article and Find Full Text PDFAdvancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review.
APL Bioeng
December 2024
Department of Mechanical Engineering, National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan.
Hyperspectral imaging (HSI) has become an evident transformative apparatus in medical diagnostics. The review aims to appraise the present advancement and challenges in HSI for medical applications. It features a variety of medical applications namely diagnosing diabetic retinopathy, neurodegenerative diseases like Parkinson's and Alzheimer's, which illustrates its effectiveness in early diagnosis, early caries detection in periodontal disease, and dermatology by detecting skin cancer.
View Article and Find Full Text PDFMachine minds: Artificial intelligence in psychiatry.
Ind Psychiatry J
August 2024
Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India.
Diagnostic and interventional aspects of psychiatric care can be augmented by the use of digital health technologies. Recent studies have tried to explore the use of artificial intelligence-driven technologies in screening, diagnosing, and treating psychiatric disorders. This short communication presents a current perspective on using Artificial Intelligence in psychiatry.
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