AIMC Topic: Machine Learning

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DeepCRISTL: deep transfer learning to predict CRISPR/Cas9 on-target editing efficiency in specific cellular contexts.

Bioinformatics (Oxford, England)
MOTIVATION: CRISPR/Cas9 technology has been revolutionizing the field of gene editing. Guide RNAs (gRNAs) enable Cas9 proteins to target specific genomic loci for editing. However, editing efficiency varies between gRNAs and so computational methods ...

MuCoCP: a priori chemical knowledge-based multimodal contrastive learning pre-trained neural network for the prediction of cyclic peptide membrane penetration ability.

Bioinformatics (Oxford, England)
MOTIVATION: There has been a burgeoning interest in cyclic peptide therapeutics due to their various outstanding advantages and strong potential for drug formation. However, it is undoubtedly costly and inefficient to use traditional wet lab methods ...

Predicting excellent response to radioiodine in differentiated thyroid cancer using machine learning.

Acta otorhinolaryngologica Italica : organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale
OBJECTIVE: If excellent response (ER) occurs after radioactive iodine (RAI) treatment in patients with differentiated thyroid carcinoma (DTC), the recurrence rate is low. Our study aims to predict ER at 6-24 months after RAI by using machine learning...

Screening of gastric cancer diagnostic biomarkers in the homologous recombination signaling pathway and assessment of their clinical and radiomic correlations.

Cancer medicine
BACKGROUND: Homologous recombination plays a vital role in the occurrence and drug resistance of gastric cancer. This study aimed to screen new gastric cancer diagnostic biomarkers in the homologous recombination pathway and then used radiomic featur...

Machine Learning-Based Prediction of 1-Year Survival Using Subjective and Objective Parameters in Patients With Cancer.

JCO clinical cancer informatics
PURPOSE: Palliative care is recommended for patients with cancer with a life expectancy of <12 months. Machine learning (ML) techniques can help in predicting survival outcomes among patients with cancer and may help distinguish who benefits the most...

Prediction of Drug-Induced Liver Injury: From Molecular Physicochemical Properties and Scaffold Architectures to Machine Learning Approaches.

Chemical biology & drug design
The process of developing new drugs is widely acknowledged as being time-intensive and requiring substantial financial investment. Despite ongoing efforts to reduce time and expenses in drug development, ensuring medication safety remains an urgent p...

Speakers-Used as sensors for detecting acoustic loads with artificial intelligence.

The Journal of the Acoustical Society of America
Previous research demonstrated the potential of using speakers as sensors to detect ear canal conditions. This study continues that effort by using a single speaker to measure electrical impedance across various acoustic loads. Electrical impedance d...

Aggregated Pattern Classification Method for improving neural disorder stage detection.

Brain and behavior
BACKGROUND: Neurological disorders pose a significant health challenge, and their early detection is critical for effective treatment planning and prognosis. Traditional classification of neural disorders based on causes, symptoms, developmental stag...

Machine learning and experimental validation of novel biomarkers for hypertrophic cardiomyopathy and cancers.

Journal of cellular and molecular medicine
Hypertrophic cardiomyopathy (HCM) is a hereditary cardiac disorder marked by anomalous thickening of the myocardium, representing a significant contributor to mortality. While the involvement of immune inflammation in the development of cardiac ailme...