AIMC Topic: Machine Learning

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GraphVelo allows for accurate inference of multimodal velocities and molecular mechanisms for single cells.

Nature communications
RNA velocities and generalizations emerge as powerful approaches for extracting time-resolved information from high-throughput snapshot single-cell data. Yet, several inherent limitations restrict applying the approaches to genes not suitable for RNA...

Circulating proteins and metabolites panel for noninvasive preoperative diagnosis of epithelial ovarian cancer.

BMC medicine
BACKGROUND: Existing biomarkers for epithelial ovarian cancer (EOC) have demonstrated limited sensitivity and specificity. This study aimed to investigate plasma protein and metabolite characteristics of EOC and identify novel biomarker candidates fo...

Development of data driven models to accurately estimate density of fatty acid ethyl esters.

Scientific reports
Fatty acid ethyl esters (FAEEs) are widely used in biofuels, pharmaceuticals, and lubricants, offering an eco-friendly alternative due to their biodegradability and renewable nature, contributing to environmental sustainability. The objective of this...

Radiomics early assessment of post chemotherapy cardiotoxicity in cancer patients using 2D echocardiography imaging an interpretable machine learning study.

Scientific reports
Cardiotoxicity is the loss of the heart muscle's ability to contract effectively, often due to chemotherapy or radiation therapy. This study uses interpretable machine learning to predict post-chemotherapy cardiotoxicity using radiomics features extr...

Use of computer vision analysis for labeling inattention periods in EEG recordings with visual stimuli.

Scientific reports
Electroencephalography (EEG) recordings with visual stimuli require detailed coding to determine the periods of participant's attention. Here we propose to use a supervised machine learning model and off-the-shelf video cameras only. We extract compu...

Predictive analysis of solubility data with pressure and temperature in assessing nanomedicine preparation via supercritical carbon dioxide.

Scientific reports
This work presents a comprehensive study on the prediction of phenytoin solubility at supercritical state using advanced techniques including machine learning analysis. The solubility of small-molecule pharmaceutical was analyzed and calculated to en...

Constructing a predictive model for acute mastitis in lactating women based on machine learning.

Scientific reports
Acute lactational mastitis is a frequently occurring complication for lactating women, exerting a certain degree of influence on their physical condition, breastfeeding, mental health, and daily life. The etiology of this disease is complex, and the ...

Machine learning-optimized dual-band wearable antenna for real-time remote patient monitoring in biomedical IoT systems.

Scientific reports
This work presents a machine learning (ML)-optimized dual-band wearable antenna designed specifically for biomedical applications in healthcare monitoring. Fabricated on a Rogers substrate of 40 × 41 mm, the antenna operates at 2.4 GHz and 5.8 GHz wi...

Machine learning enhanced expert system for detecting heart failure decompensation using patient reported vitals and electronic health records.

Scientific reports
Heart failure (HF) is a condition with periods of stability interrupted by periods of worsening symptoms, known as decompensation episodes. Digital interventions are promising tools to alleviate burdens on HF management through automated alerts at th...

Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study.

Translational psychiatry
Previous studies have found that major depressive disorder (MDD) may accelerate overall structural brain aging. Nevertheless, it still remains unknown whether anhedonia, a critical negative prognostic indicator in MDD, further leads to advanced brain...