Multimodal biomedical AI
The increasing availability of biomedical data from large biobanks, electronic health records,
medical imaging, wearable and ambient biosensors, and the lower cost of genome and …
medical imaging, wearable and ambient biosensors, and the lower cost of genome and …
Enhancing head and neck tumor management with artificial intelligence: Integration and perspectives
NN Zhong, HQ Wang, XY Huang, ZZ Li, LM Cao… - Seminars in Cancer …, 2023 - Elsevier
Head and neck tumors (HNTs) constitute a multifaceted ensemble of pathologies that
primarily involve regions such as the oral cavity, pharynx, and nasal cavity. The intricate …
primarily involve regions such as the oral cavity, pharynx, and nasal cavity. The intricate …
Artificial intelligence to bring nanomedicine to life
N Serov, V Vinogradov - Advanced Drug Delivery Reviews, 2022 - Elsevier
The technology of drug delivery systems (DDSs) has demonstrated an outstanding
performance and effectiveness in production of pharmaceuticals, as it is proved by many …
performance and effectiveness in production of pharmaceuticals, as it is proved by many …
Functional magnetic resonance imaging, deep learning, and Alzheimer's disease: A systematic review
SL Warren, AA Moustafa - Journal of Neuroimaging, 2023 - Wiley Online Library
Alzheimer's disease (AD) is currently diagnosed using a mixture of psychological tests and
clinical observations. However, these diagnoses are not perfect, and additional diagnostic …
clinical observations. However, these diagnoses are not perfect, and additional diagnostic …
Artificial Intelligence and Diabetic Retinopathy: AI Framework, prospective studies, head-to-head validation, and cost-effectiveness
Current guidelines recommend that individuals with diabetes receive yearly eye exams for
detection of referable diabetic retinopathy (DR), one of the leading causes of new-onset …
detection of referable diabetic retinopathy (DR), one of the leading causes of new-onset …
A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future
RJ Woodman, AA Mangoni - Aging Clinical and Experimental Research, 2023 - Springer
The increasing access to health data worldwide is driving a resurgence in machine learning
research, including data-hungry deep learning algorithms. More computationally efficient …
research, including data-hungry deep learning algorithms. More computationally efficient …
Machine-learning-based adverse drug event prediction from observational health data: A review
Adverse drug events (ADEs) are responsible for a significant number of hospital admissions
and fatalities. Machine learning models have been developed to assess individual patient …
and fatalities. Machine learning models have been developed to assess individual patient …
Emerging applications of machine learning in genomic medicine and healthcare
The integration of artificial intelligence technologies has propelled the progress of clinical
and genomic medicine in recent years. The significant increase in computing power has …
and genomic medicine in recent years. The significant increase in computing power has …
[HTML][HTML] Brain simulation as a cloud service: The Virtual Brain on EBRAINS
M Schirner, L Domide, D Perdikis, P Triebkorn… - NeuroImage, 2022 - Elsevier
Abstract The Virtual Brain (TVB) is now available as open-source services on the cloud
research platform EBRAINS (ebrains. eu). It offers software for constructing, simulating and …
research platform EBRAINS (ebrains. eu). It offers software for constructing, simulating and …
Artificial intelligence in metabolomics: A current review
Metabolomics and artificial intelligence (AI) form a synergistic partnership. Metabolomics
generates large datasets comprising hundreds to thousands of metabolites with complex …
generates large datasets comprising hundreds to thousands of metabolites with complex …