AIMC Topic: Machine Learning

Clear Filters Showing 29191 to 29200 of 34417 articles

[Construction of recognition models for subthreshold depression based on multiple machine learning algorithms and vocal emotional characteristics].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVES: To construct vocal recognition classification models using 6 machine learning algorithms and vocal emotional characteristics of individuals with subthreshold depression to facilitate early identification of subthreshold depression.

Study on the mechanism of action of the active ingredient of Calculus Bovis in the treatment of sepsis by integrating single-cell sequencing and machine learning.

Medicine
BACKGROUND: Sepsis, a complex inflammatory condition with high mortality rates, lacks effective treatments. This study explores the therapeutic mechanisms of Calculus Bovis in sepsis using network pharmacology and RNA sequencing.

Identification of a telomere-related gene signature for the prognostic and immune landscape prediction in head and neck squamous cell carcinoma by integrated analysis of machine learning and Mendelian randomization.

Medicine
Telomere-related genes (TRGs) are vital in diverse tumor types. Nevertheless, there is a notable lack of in-depth research concerning their significance in head and neck squamous cell carcinoma (HNSCC). In this context, the present study aims to asse...

Utilizing Artificial Intelligence for Predicting Postoperative Complications in Breast Reduction Surgery: A Comprehensive Retrospective Analysis of Predictive Features and Outcomes.

Aesthetic surgery journal
BACKGROUND: Breast reduction is a common procedure with growing rates in the United States of America, aimed at alleviating the physical and psychological burdens of macromastia. Despite high success rates, it carries a risk of complications, with in...

PenoMeter: a machine learning and algorithmic tool to advance Peyronie's disease assessment.

The journal of sexual medicine
BACKGROUND: Peyronie's disease curvature assessment is a critical step for patient assessment; however, tools for objective, unbiased, and reproducible quantification are currently limited.

[Advancements in machine learning applications in refractive surgery].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
Refractive error is a significant factor contributing to visual impairment, imposing a relatively large burden on the social economy. Although refractive surgery is an important corrective method, it faces challenges in clinical practice, such as pre...

Examination of the relationship between D-amino acid profiles and cognitive function in individuals with mild cognitive impairment: a machine learning approach.

The international journal of neuropsychopharmacology
BACKGROUND: The global prevalence of dementia is significantly increasing. Early detection and prevention strategies, particularly for mild cognitive impairment (MCI), are crucial but currently hindered by the lack of established biomarkers. Here, we...

Artificial neural networks to predict the presence of Neosporosis in cattle.

Mathematical biosciences and engineering : MBE
The prediction of bovine infectious diseases is a constant challenge as generally, only laboratory data is available not allowing the study of their relationship with each disease's risk factors. The diseases neosporosis and bovine viral diarrhea, wh...

Automated Fall Detection in Smart Homes Using Multiple Radars and Machine Learning Classifiers.

Studies in health technology and informatics
Falls pose a significant risk, especially among elderly persons. Recently, radar sensors have been explored for fall detection. In this study, an attempt has been made to classify fall detection using multiple radars, machine learning (ML) classifier...

Using Machine Learning to Predict Survival in Patients with Metastatic Castration-Resistant Prostate Cancer.

Studies in health technology and informatics
Non-specific clinical biomarkers have been shown to help identify prognostic risks in cancer patients. However, the accuracy of prognostic biomarkers for predicting survival in patients with metastatic castration-resistant prostate cancer (mCRPC) sti...