AIMC Topic: Machine Learning

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Artificial Intelligence for Upper Aerodigestive Tract Endoscopy and Laryngoscopy: A Guide for Physicians and State-of-the-Art Review.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: The endoscopic and laryngoscopic examination is paramount for laryngeal, oropharyngeal, nasopharyngeal, nasal, and oral cavity benign lesions and cancer evaluation. Nevertheless, upper aerodigestive tract (UADT) endoscopy is intrinsically ...

Science-Driven Atomistic Machine Learning.

Angewandte Chemie (International ed. in English)
Machine learning (ML) algorithms are currently emerging as powerful tools in all areas of science. Conventionally, ML is understood as a fundamentally data-driven endeavour. Unfortunately, large well-curated databases are sparse in chemistry. In this...

Calcification Detection in Intravascular Ultrasound (IVUS) Images Using Transfer Learning Based MultiSVM model.

Ultrasonic imaging
Cardiovascular disease serves as the leading cause of death worldwide. Calcification detection is considered an important factor in cardiovascular diseases. Currently, medical practitioners visually inspect the presence of calcification using intrava...

Spectral Classification of Large-Scale Blended (Micro)Plastics Using FT-IR Raw Spectra and Image-Based Machine Learning.

Environmental science & technology
Microplastics (MPs) are currently recognized as emerging pollutants; their identification and classification are therefore essential during their monitoring and management. In contrast to most studies based on small datasets and library searches, thi...

Generalization of vision pre-trained models for histopathology.

Scientific reports
Out-of-distribution (OOD) generalization, especially for medical setups, is a key challenge in modern machine learning which has only recently received much attention. We investigate how different convolutional pre-trained models perform on OOD test ...

Label-free liquid biopsy through the identification of tumor cells by machine learning-powered tomographic phase imaging flow cytometry.

Scientific reports
Image-based identification of circulating tumor cells in microfluidic cytometry condition is one of the most challenging perspectives in the Liquid Biopsy scenario. Here we show a machine learning-powered tomographic phase imaging flow cytometry syst...

Improved accuracy and less fault prediction errors via modified sequential minimal optimization algorithm.

PloS one
The benefits and opportunities offered by cloud computing are among the fastest-growing technologies in the computer industry. Additionally, it addresses the difficulties and issues that make more users more likely to accept and use the technology. T...

Graph-based machine learning improves just-in-time defect prediction.

PloS one
The increasing complexity of today's software requires the contribution of thousands of developers. This complex collaboration structure makes developers more likely to introduce defect-prone changes that lead to software faults. Determining when the...

Understanding the Impact of Aging on Attractiveness Using a Machine Learning Model of Facial Age Progression.

Facial plastic surgery & aesthetic medicine
Advances in machine learning age progression technology offer the unique opportunity to better understand the public's perception on the aging face. To compare how observers perceive attractiveness and traditional gender traits in faces created wit...

A consensual machine-learning-assisted QSAR model for effective bioactivity prediction of xanthine oxidase inhibitors using molecular fingerprints.

Molecular diversity
Xanthine oxidase inhibitors (XOIs) have been widely studied due to the promising potential as safe and effective therapeutics in hyperuricemia and gout. Currently, available XOI molecules have been developed from different experiments but they are wi...