AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Mental Recall

Showing 31 to 40 of 72 articles

Clear Filters

Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment.

Journal of Alzheimer's disease : JAD
BACKGROUND: Amyloid-β (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer's disease. However, Aβ evaluation through Aβ positron emission tomography (PET) is limited due to high cos...

The current state of memory Specificity Training (MeST) for emotional disorders.

Current opinion in psychology
Memory Specificity Training (MeST) is an intervention developed from basic science that has found clinical utility. MeST uses cued recall exercises to target the difficulty that some people with emotional disorders have in recalling personally experi...

A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.

Nutrients
BACKGROUND: Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration pneumonia. This study aimed to develop a simple screening test using image recognition with a low r...

Audit lead selection and yield prediction from historical tax data using artificial neural networks.

PloS one
Tax audits are a crucial process adopted in all tax departments to ensure tax compliance and fairness. Traditionally, tax audit leads have been selected based on empirical rules and randomization methods, which are not adaptive, may miss major cases ...

Integration of Neighbor Topologies Based on Meta-Paths and Node Attributes for Predicting Drug-Related Diseases.

International journal of molecular sciences
Identifying new disease indications for existing drugs can help facilitate drug development and reduce development cost. The previous drug-disease association prediction methods focused on data about drugs and diseases from multiple sources. However,...

White Matter Lesion Segmentation for Multiple Sclerosis Patients implementing deep learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The aim of this work is to address the problem of White Matter Lesion (WML) segmentation employing Magnetic Resonance Imaging (MRI) images from Multiple Sclerosis (MS) patients through the application of deep learning. A U-net based architecture cont...

Utilizing Deep Learning on Limited Mobile Speech Recordings for Detection of Obstructive Pulmonary Disease.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Passive assessment of obstructive pulmonary disease has gained substantial interest over the past few years in the mobile and wearable computing communities. One of the promising approaches is speech-based pulmonary assessment wherein spontaneous or ...

Hybrid-Enhanced Siamese Similarity Models in Ligand-Based Virtual Screen.

Biomolecules
Information technology has become an integral aspect of the drug development process. The virtual screening process (VS) is a computational technique for screening chemical compounds in a reasonable amount of time and cost. The similarity search is o...

Associative memory of structured knowledge.

Scientific reports
A long standing challenge in biological and artificial intelligence is to understand how new knowledge can be constructed from known building blocks in a way that is amenable for computation by neuronal circuits. Here we focus on the task of storage ...

Machine learning classifiers for electrode selection in the design of closed-loop neuromodulation devices for episodic memory improvement.

Cerebral cortex (New York, N.Y. : 1991)
Successful neuromodulation approaches to alter episodic memory require closed-loop stimulation predicated on the effective classification of brain states. The practical implementation of such strategies requires prior decisions regarding electrode im...