AIMC Topic: Machine Learning

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Smart photonic crystal fiber optical sensor for tuberculosis detection with machine learning integration.

Scientific reports
One of the most common infectious disease-related causes of death globally, particularly in low- and middle-income nations, persists: tuberculosis. At a manifestation of globalization, causes of death keep growing. As it happens, we have developed a ...

Evaluation of various traditional machine learning techniques for predicting the acute effect of different hamstring muscle stretching methods among male soccer players.

Scientific reports
This study investigated the acute effects of static (SS), dynamic (DS), and ballistic (BS) hamstring stretching on performance in male soccer players and applied machine learning (ML) to predict protocol efficacy. A total of 249 players with and with...

Faecal metabolites as a readout of habitual diet capture dietary interactions with the gut microbiome.

Nature communications
The interplay between diet and gut microbiome composition is complex. Faecal metabolites, the end products of human and microbial metabolism, provide insights into these interactions. Here, we integrate faecal metabolomics, metagenomics, and habitual...

Automated Speech Analysis for Screening and Monitoring Bipolar Depression: Machine Learning Model Development and Interpretation Study.

JMIR medical informatics
BACKGROUND: Depressive episodes in bipolar disorder are frequent, prolonged, and contribute substantially to functional impairment and reduced quality of life. Therefore, early and objective detection of bipolar depression is critical for timely inte...

Machine Learning-Based Prediction of In-Hospital Falls in Adult Inpatients: Retrospective Observational Multicenter Study.

JMIR medical informatics
BACKGROUND: Falls among hospitalized patients are a critical issue that often leads to prolonged hospital stays and increased health care costs. Traditional fall risk assessments typically rely on standardized scoring systems; however, these may fail...

Artificial inteligence reading of cystometric traces provides good correlation with human diagnosis.

World journal of urology
AIM: Urodynamic studies are essential for diagnosing lower urinary tract dysfunction but are expert-dependent and time-consuming. Artificial intelligence (AI), notably machine learning (ML) and deep learning (DL) may help automate and standardize int...

An automated classification of brain white matter inherited disorders (Leukodystrophy) using MRI image features.

Biomedical physics & engineering express
Leukodystrophies are a group of inherited disorders that predominantly and selectively affect the white matter of the central nervous system. Their overlapping clinical and imaging manifestations make a timely and accurate diagnosis challenging. In t...

Abnormal brain network reconfiguration in neuropsychiatric disorders across cognitive decline, Depression, and Schizophrenia.

PloS one
OBJECTIVE: Neuropsychiatric disorders are characterized by high complexity and comorbidity, imposing a substantial burden on both patients and society. However, their elusive pathogenic mechanisms impede accurate clinical diagnosis and effective inte...

Identification and validation of palmitoylation-related signature genes based on machine learning for prostate cancer.

PloS one
Prostate cancer (PCa) remains a leading cause of cancer-related mortality in men, with challenges in diagnosis and treatment due to tumor heterogeneity. This study identifies palmitoylation-related signature genes as potential diagnostic and therapeu...