Mr.Chongwei Shi Enhances Genomic Analysis Through Signal Processing and Machine Learning Integration for Gene Identification

A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral ...

Unveiling schizophrenia's neural and mental signatures with machine learning

Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking patterns and altered perceptions of reality, as well as mental impairments.
AZoOptics

Deep Learning in Optical Microscopy: Advancements and Applications

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...
Proceedings of the National Academy of Sciences (PNAS)

Identifying variation in dinosaur footprints and classifying problematic specimens via unbiased unsupervised machine learning

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...

Mapping cell development with mathematics-informed machine learning

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...
IEEE

Intelligent Human Gait Phase Classification Using Machine Learning Models

Abstract: Advancements in machine learning (ML) have facilitated the prediction of key aspects of human locomotion, particularly in identifying subject gait trajectories essential for recognizing ...

Machine-learning analysis reclassifies armed conflicts into three new archetypes

There is often no straightforward explanation for the various types of violence that occur around the world. In fact, even when using clear definitions (such as “Civil War,” “Invasion,” or “Local ...
European Medical Journal

Novel Biomarkers Improve Depression Diagnosis Accuracy

New TMS biomarkers combined with machine learning accurately classified major depressive disorder. Learn more about this ...
IEEE

Machine Learning-Based Classification of Suspension Droplet-Solid Wall Impacts for Control of Droplet Fragmentation

Abstract: This study explores the collision of suspension droplets against solid dry surfaces (substrates). It applies and compares multiple machine learning (ML) models for the classification of ...
The Lancet

Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study ...

aDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for ...