AIMC Topic: Machine Learning

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Stable feature selection utilizing Graph Convolutional Neural Network and Layer-wise Relevance Propagation for biomarker discovery in breast cancer.

Artificial intelligence in medicine
High-throughput technologies are becoming increasingly important in discovering prognostic biomarkers and in identifying novel drug targets. With Mammaprint, Oncotype DX, and many other prognostic molecular signatures breast cancer is one of the para...

Application of artificial intelligence in dental implant prognosis: A scoping review.

Journal of dentistry
OBJECTIVES: The purpose of this scoping review was to evaluate the performance of artificial intelligence (AI) in the prognosis of dental implants.

Waste to resource: Mining antimicrobial peptides in sludge from metagenomes using machine learning.

Environment international
The emergence of antibiotic-resistant bacteria poses a huge threat to the treatment of infections. Antimicrobial peptides are a class of short peptides that widely exist in organisms and are considered as potential substitutes for traditional antibio...

Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence.

Molecular pharmaceutics
Understanding protein sequence and structure is essential for understanding protein-protein interactions (PPIs), which are essential for many biological processes and diseases. Targeting protein binding hot spots, which regulate signaling and growth,...

Development and validation of 'Patient Optimizer' (POP) algorithms for predicting surgical risk with machine learning.

BMC medical informatics and decision making
BACKGROUND: Pre-operative risk assessment can help clinicians prepare patients for surgery, reducing the risk of perioperative complications, length of hospital stay, readmission and mortality. Further, it can facilitate collaborative decision-making...

Combination prediction method of students' performance based on ant colony algorithm.

PloS one
Students' performance is an important factor for the evaluation of teaching quality in colleges. The prediction and analysis of students' performance can guide students' learning in time. Aiming at the low accuracy problem of single model in students...

Enhancing site selection strategies in clinical trial recruitment using real-world data modeling.

PloS one
Slow patient enrollment or failing to enroll the required number of patients is a disruptor of clinical trial timelines. To meet the planned trial recruitment, site selection strategies are used during clinical trial planning to identify research sit...

The infant health effects of doulas: Leveraging big data and machine learning to inform cost-effective targeting.

Health economics
Doula services represent an underutilized maternal and child health intervention with the potential to improve outcomes through the provision of physical, emotional, and informational support. However, there is limited evidence of the infant health e...

Monitoring multistage healthcare processes using state space models and a machine learning based framework.

Artificial intelligence in medicine
Monitoring healthcare processes, such as surgical outcomes, with a keen focus on detecting changes and unnatural conditions at an early stage is crucial for healthcare professionals and administrators. In line with this goal, control charts, which ar...