AIMC Topic: Humans

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Deep fusion based transfer learning with bald eagle search algorithm for sign language recognition to assist individuals with hearing and speech impairments.

Scientific reports
Sign language (SL) is a significant communication method for individuals with hearing impairments, using hand gestures to convey letters, words, and sentences. However, several people are unfamiliar with SL, creating a communication gap. An intellige...

Structure based drug design and machine learning approaches for identifying natural inhibitors against the human αβIII tubulin isotype.

Scientific reports
Microtubules (MTs) play a crucial role in mitosis and are composed of α-/β-tubulin heterodimeric subunits. In eukaryotes, eight α-tubulin and ten β-tubulin isotypes have been reported, each displaying tissue-specific expression patterns. Among them, ...

Using AI to Summarize US Presidential Campaign TV Advertisement Videos, 1952-2012.

Scientific data
This paper introduces the largest and most comprehensive dataset of US presidential campaign television advertisements, available in digital format. The dataset also includes machine-searchable transcripts and high-quality summaries designed to facil...

A foundation model for human-AI collaboration in medical literature mining.

Nature communications
Applying artificial intelligence (AI) for systematic literature review holds great potential for enhancing evidence-based medicine, yet has been limited by insufficient training and evaluation. Here, we present LEADS, an AI foundation model trained o...

Machine learning and data-driven inverse modeling of metabolomics unveil key processes of active aging.

NPJ systems biology and applications
Physical inactivity and low fitness have become global health concerns. Metabolomics, as an integrative approach, may link fitness to molecular changes. In this study, we analyzed blood metabolomes from elderly individuals under different treatments....

Development of deep learning-based narrow-band imaging endocytoscopic classification for predicting colorectal lesions from a retrospective study.

Nature communications
Data-driven approaches have advanced colorectal lesion diagnosis in digestive endoscopy, yet their application in endocytoscopy (EC)-a high-magnification imaging technique-remains limited, with most studies relying on conventional machine learning me...

Diabetic Foot Ulcer Classification Models Using Artificial Intelligence and Machine Learning Techniques: Systematic Review.

Journal of medical Internet research
BACKGROUND: Diabetes-related foot ulceration (DFU) is a common complication of diabetes, with a significant impact on survival, health care costs, and health-related quality of life. The prognosis of DFU varies widely among individuals. The Internati...

Extension of the Consolidated Criteria for Reporting Qualitative Research Guideline to Large Language Models (COREQ+LLM): Protocol for a Multiphase Study.

JMIR research protocols
BACKGROUND: Qualitative research provides essential insights into human behaviors, perceptions, and experiences in health sciences. The COREQ (Consolidated Criteria for Reporting Qualitative Research) checklist, published in 2007 and endorsed by the ...

Machine Learning in Health Economic Evaluations: Protocol for a Scoping Review.

JMIR research protocols
BACKGROUND: In recent years, the development of machine learning (ML) applications has increased substantially, indicating the potential role of ML in transforming health care. However, the integration of ML approaches into health economic evaluation...

Improving the Reporting Quality of Studies on Information Extraction From Clinical Texts: Protocol for the Development of a Consensus-Based Reporting Guideline.

JMIR research protocols
BACKGROUND: Information extraction (IE) from clinical texts is increasingly important in health care; yet, reporting practices remain inconsistent. Existing guidelines do not fully address the unique challenges of IE studies. IE methods vary widely i...