Deep learning (DL) techniques are becoming more popular for diagnosing Parkinson's disease (PD) because they offer non-invasive and easily accessible tools. By using advanced data analysis, these methods improve early detection and diagnosis, which i...
Pregnancy termination is still a sensitive and continuing public health issue due to several political, economic, religious, and social concerns. This study assesses the applications of machine learning models in the prediction of pregnancy terminati...
Health-related quality of life (HRQol) is a crucial dimension of care outcomes. Many HRQoL measures exist, but methodological and implementation challenges impede primary care (PC) use. We aim to develop and evaluate a novel machine learning (ML) alg...
This study introduces a novel method for predicting the Big Five personality traits through the analysis of speech samples, advancing the field of computational personality assessment. We collected data from 2045 participants who completed a self-rep...
Trastuzumab (Tra)-induced cardiotoxicity (TIC) is a serious side effect of cancer chemotherapy, which can seriously harm the health of cancer patients. However, there is currently a lack of effective and reliable biomarkers for the early diagnosis of...
The array of complex and evolving patient data has limited clinical decision making in the emergency department (ED). This study introduces an advanced deep learning algorithm designed to enhance real-time prediction accuracy for integration into a n...
Machine Learning (ML) techniques require novel computer programming skills along with clinical domain knowledge to produce a useful model. We demonstrate the use of a cloud-based ML tool that does not require any programming expertise to develop, val...
Medical science monitor : international medical journal of experimental and clinical research
Dec 3, 2024
BACKGROUND Predicting 24-hour intraocular pressure (IOP) fluctuations is crucial for enhancing glaucoma management. Traditional methods of measuring 24-hour IOP fluctuations are complex and present certain limitations. The present study leverages mac...
The latest developments combining deep learning technology and medical image data have attracted wide attention and provide efficient noninvasive methods for the early diagnosis of breast cancer. The success of this task often depends on a large amou...
OBJECTIVE: The rapid development of Artificial Intelligence (AI) has raised questions about its potential uses in different sectors of everyday life. Specifically in medicine, the question arose whether chatbots could be used as tools for clinical de...
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