AIMC Topic: Humans

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Enhancing polyp classification: A comparative analysis of spatio-temporal techniques.

Medical engineering & physics
Colorectal cancer (CRC) is a major health concern, ranking as the third deadliest cancer globally. Early diagnosis of adenomatous polyps which are pre-cancerous abnormal tissue growth, is crucial for preventing CRC. Artificial intelligence-assisted n...

Synthetic Data in Healthcare and Drug Development: Definitions, Regulatory Frameworks, Issues.

CPT: pharmacometrics & systems pharmacology
With the recent and evolving regulatory frameworks regarding the usage of Artificial Intelligence (AI) in both drug and medical device development, the differentiation between data derived from observed ('true' or 'real') sources and artificial data ...

Artificial intelligence strategies based on random forests for detection of AI-generated content in public health.

Public health
OBJECTIVES: To train and test a Random Forest machine learning model with the ability to distinguish AI-generated from human-generated textual content in the domain of public health, and public health policy.

Single-Component Double-Emissive Ratiometric Probe: Toward Machine Learning Driven Detection and Discrimination of Neurological Biomarkers.

Analytical chemistry
This study presents an attractive single-component ratiometric fluorescent sensor that utilizes the oxidation of BSA-protected Au nanoclusters (BSA-Au NCs) by -Bromosuccinimide (NBS) to detect catecholamine neurotransmitters and their metabolites, wh...

Supporting Speech-Language Pathologists in Schools With Interdisciplinary Team Science: A Viewpoint From the National Artificial Intelligence Institute for Exceptional Education.

Language, speech, and hearing services in schools
PURPOSE: Complex scientific problems, including those facing the discipline of communication sciences and disorders (CSD), require interdisciplinary teams of scientists who bring diverse perspectives, knowledge, and skills. According to a recent surv...

Combining multi-omics analysis with machine learning to uncover novel molecular subtypes, prognostic markers, and insights into immunotherapy for melanoma.

BMC cancer
BACKGROUND: Melanoma (SKCM) is an extremely aggressive form of cancer, characterized by high mortality rates, frequent metastasis, and limited treatment options. Our study aims to identify key target genes and enhance the diagnostic accuracy of melan...

CNRein: an evolution-aware deep reinforcement learning algorithm for single-cell DNA copy number calling.

Genome biology
Low-pass single-cell DNA sequencing technologies and algorithmic advancements have enabled haplotype-specific copy number calling on thousands of cells within tumors. However, measurement uncertainty may result in spurious CNAs inconsistent with real...

Prediction of new-onset migraine using clinical-genotypic data from the HUNT Study: a machine learning analysis.

The journal of headache and pain
BACKGROUND: Migraine is associated with a range of symptoms and comorbid disorders and has a strong genetic basis, but the currently identified risk loci only explain a small portion of the heritability, often termed the "missing heritability". We ai...

scAMZI: attention-based deep autoencoder with zero-inflated layer for clustering scRNA-seq data.

BMC genomics
BACKGROUND: Clustering scRNA-seq data plays a vital role in scRNA-seq data analysis and downstream analyses. Many computational methods have been proposed and achieved remarkable results. However, there are several limitations of these methods. First...

Speech emotion recognition with light weight deep neural ensemble model using hand crafted features.

Scientific reports
Automatic emotion detection has become crucial in various domains, such as healthcare, neuroscience, smart home technologies, and human-computer interaction (HCI). Speech Emotion Recognition (SER) has attracted considerable attention because of its p...