AIMC Topic: Humans

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Genomic language models: opportunities and challenges.

Trends in genetics : TIG
Large language models (LLMs) are having transformative impacts across a wide range of scientific fields, particularly in the biomedical sciences. Just as the goal of natural language processing is to understand sequences of words, a major objective i...

Automatic Segmentation of Vestibular Schwannoma From MRI Using Two Cascaded Deep Learning Networks.

The Laryngoscope
OBJECTIVE: Automatic segmentation and detection of vestibular schwannoma (VS) in MRI by deep learning is an upcoming topic. However, deep learning faces generalization challenges due to tumor variability even though measurements and segmentation of V...

A novel vessel enhancement method based on Hessian matrix eigenvalues using multilayer perceptron.

Bio-medical materials and engineering
BACKGROUND: Vessel segmentation is a critical aspect of medical image processing, often involving vessel enhancement as a preprocessing step. Existing vessel enhancement methods based on eigenvalues of Hessian matrix face challenges such as inconsist...

Convolutional Neural Networks for the segmentation of hippocampal structures in postmortem MRI scans.

Journal of neuroscience methods
BACKGROUND: The hippocampus plays a crucial role in memory and is one of the first structures affected by Alzheimer's disease. Postmortem MRI offers a way to quantify the alterations by measuring the atrophy of the inner structures of the hippocampus...

Success History Adaptive Competitive Swarm Optimizer with Linear Population Reduction: Performance benchmarking and application in eye disease detection.

Computers in biology and medicine
Eye disease detection has achieved significant advancements thanks to artificial intelligence (AI) techniques. However, the construction of high-accuracy predictive models still faces challenges, and one reason is the deficiency of the optimizer. Thi...

A novel fuzzy three-valued logic computational framework in machine learning for medicine dataset.

Computers in biology and medicine
For consideration of uncertainties of a medicine dataset, a new conceptual architecture fuzzy three-valued logic is introduced in this research work. The proposed concept is applied to the heart disease dataset for the assessment of heart disease ris...

Attention-guided CenterNet deep learning approach for lung cancer detection.

Computers in biology and medicine
Lung cancer remains a significant health concern worldwide, prompting ongoing research efforts to enhance early detection and diagnosis. Prior studies have identified key challenges in existing approaches, including limitations in feature extraction,...

Classification of non-TCGA cancer samples to TCGA molecular subtypes using compact feature sets.

Cancer cell
Molecular subtypes, such as defined by The Cancer Genome Atlas (TCGA), delineate a cancer's underlying biology, bringing hope to inform a patient's prognosis and treatment plan. However, most approaches used in the discovery of subtypes are not suita...

Artificial intelligence, recessionary pressures and population health.

Bulletin of the World Health Organization
Economic and labour policies have a considerable influence on health and well-being through direct financial impacts, and by shaping social and physical environments. Strong economies are important for public health investment and employment, yet the...

Drug repositioning for Parkinson's disease: An emphasis on artificial intelligence approaches.

Ageing research reviews
Parkinson's disease (PD) is one of the most incapacitating neurodegenerative diseases (NDDs). PD is the second most common NDD worldwide which affects approximately 1-2 percent of people over 65 years. It is an attractive pursuit for artificial intel...