AIMC Topic: Algorithms

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Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms.

Medicine
This research aims to enhance our comprehensive understanding of the influence of type-2 diabetes on the development of cardiovascular diseases (CVD) risk, its underlying determinants, and to construct precise predictive models capable of accurately ...

SAMP: Identifying antimicrobial peptides by an ensemble learning model based on proportionalized split amino acid composition.

Briefings in functional genomics
It is projected that 10 million deaths could be attributed to drug-resistant bacteria infections in 2050. To address this concern, identifying new-generation antibiotics is an effective way. Antimicrobial peptides (AMPs), a class of innate immune eff...

Eye-Rubbing Detection Tool Using Artificial Intelligence on a Smartwatch in the Management of Keratoconus.

Translational vision science & technology
PURPOSE: Eye rubbing is considered to play a significant role in the progression of keratoconus and of corneal ectasia following refractive surgery. To our knowledge, no tool performs an objective quantitative evaluation of eye rubbing using a device...

GENNDTI: Drug-Target Interaction Prediction Using Graph Neural Network Enhanced by Router Nodes.

IEEE journal of biomedical and health informatics
Identifying drug-target interactions (DTI) is crucial in drug discovery and repurposing, and in silico techniques for DTI predictions are becoming increasingly important for reducing time and cost. Most interaction-based DTI models rely on the guilt-...

ANALYSIS OF CHALLENGES AND POSSIBILITIES OF USING ARTIFICIAL INTELLIGENCE IN MEDICAL DIAGNOSTICS.

Georgian medical news
BACKGROUND: This study aims to analyze the geographical distribution of different AI types and applications, document implementation challenges, and assess outcomes of interest as well as potential opportunities for increasing healthcare efficiency.

Assessing diagnostic performance for common skin diseases using an AI-assisted tele-expertise platform: a proof of concept.

European journal of dermatology : EJD
Advancements in machine learning (ML) are making artificial intelligence more feasible in dermatology, with promising results for diagnosing skin cancers, though few studies cover common or inflammatory dermatoses. To evaluate the diagnostic accuracy...

Evaluation of machine learning algorithms and computational structural validation of CYP2D6 in predicting the therapeutic response to tamoxifen in breast cancer.

European review for medical and pharmacological sciences
OBJECTIVE: CYP2D6 plays a critical role in metabolizing tamoxifen into its active metabolite, endoxifen, which is crucial for its therapeutic effect in estrogen receptor-positive breast cancer. Single nucleotide polymorphisms (SNPs) in the CYP2D6 gen...

A Respiratory Signal Monitoring Method Based on Dual-Pathway Deep Learning Networks in Image-Guided Robotic-Assisted Intervention System.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Percutaneous puncture procedures, guided by image-guided robotic-assisted intervention (IGRI) systems, are susceptible to disruptions in patients' respiratory rhythm due to factors such as pain and psychological distress.

A Spatial Registration Method Based on Point Cloud and Deep Learning for Augmented Reality Neurosurgical Navigation.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: In order to achieve spatial registration for surgical navigation, a spatial registration method based on point cloud and deep learning is proposed.

Hybrid of Deep Feature Extraction and Machine Learning Ensembles for Imbalanced Skin Cancer Datasets.

Experimental dermatology
Skin cancer remains one of the most common and deadly forms of cancer, necessitating accurate and early diagnosis to improve patient outcomes. In order to improve classification performance on unbalanced datasets, this study proposes a distinctive ap...