AIMC Topic: Machine Learning

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Multi-omics and machine learning identify FN1 and ALDH2 as diagnostic biomarkers and therapeutic targets in early and late diabetic kidney disease.

Renal failure
Diabetic kidney disease (DKD), the leading cause of end-stage kidney disease worldwide, demands deeper molecular characterization to improve clinical management. This study employed an integrated multi-omics approach to identify stage-specific biomar...

IR Spectroscopy: From Experimental Spectra to High-Resolution Structural Analysis by Integrating Simulations and Machine Learning.

The journal of physical chemistry. B
Understanding biomolecular function at the atomic scale requires detailed insight into the structural changes underlying dynamic processes. Vibrational infrared (IR) spectroscopy─when paired with biomolecular simulations and quantum-chemical calculat...

Multimodal contrastive learning on rs-fMRI to quantify whole-brain network recovery after hypothalamic hamartoma surgery.

Biomedical engineering online
INTRODUCTION: Epilepsy due to hypothalamic hamartoma (HH) is associated with epileptic encephalopathy and often requires surgical intervention, as medications are ineffective at reducing the seizures. However, the first step of disentangling the impa...

From past to future: a review of methods for assessing physical activity energy expenditure.

Journal of health, population, and nutrition
BACKGROUND: Physical activity energy expenditure (PAEE) assessment is important for helping individuals maintain energy balance. This study adopts a technological evolution perspective to systematically examine the historical evolution and current pr...

New lung ultrasound system for rapid triage of pulmonary disease without a radiologist or sonographer.

BMC pulmonary medicine
BACKGROUND: Most people in the world lack access to medical imaging including for assessment of pulmonary disease. We sought to improve access to pulmonary imaging by developing a rapid automated system for triage of pulmonary disease using lung ultr...

Machine learning in biological research: key algorithms, applications, and future directions.

BMC biology
Machine learning is a robust framework to analyze questions using complex data in a variety of fields. We present definitions and recent applications of four key machine learning methods and discuss their advantages and challenges in biological resea...

BRCAGenie: A machine learning-driven 43-gene polygenic risk score model for precision prediction of breast cancer survival.

Journal of translational medicine
BACKGROUND: Breast cancer is one of the most prevalent malignancies globally, imposing a substantial disease burden. Its inherent heterogeneity complicates prognosis and treatment, underscoring the need for accurate survival prediction models to guid...

Adversarial susceptibility analysis for water quality prediction models.

Scientific reports
Water quality is a critical factor for human health and environmental sustainability. Rapid urbanization and industrialization have led to significant water contamination, increasing the prevalence of waterborne diseases. This study investigates the ...

Pitfalls in using ML to predict cognitive function performance.

Scientific reports
Machine learning analyses are widely used for predicting cognitive abilities, yet there are pitfalls that need to be considered during their implementation and interpretation of the results. Hence, the present study aimed at drawing attention to the ...

Plantar pressure distribution can be used to identify sarcopenia in maintenance hemodialysis patients.

Scientific reports
Patients undergoing maintenance hemodialysis (MHD) often suffer from sarcopenia, which affects their balance and significantly increases the risk of falls and death. Actively identifying sarcopenia, understanding the relationship between sarcopenia a...