Application of machine learning in healthcare and medicine: A review
This extensive literature review investigates the integration of Machine Learning (ML) into
the healthcare sector, uncovering its potential, challenges, and strategic resolutions. The …
the healthcare sector, uncovering its potential, challenges, and strategic resolutions. The …
[HTML][HTML] Modified meta heuristic BAT with ML classifiers for detection of autism spectrum disorder
ASD (autism spectrum disorder) is a complex developmental and neurological disorder that
impacts the social life of the affected person by disturbing their capability for interaction and …
impacts the social life of the affected person by disturbing their capability for interaction and …
[HTML][HTML] Comparison of Convolutional Neural Networks and Support Vector Machines on Medical Data: A Review
Medical image processing has become an integral part of disease diagnosis, where
technological advancements have brought significant changes to this approach. In this …
technological advancements have brought significant changes to this approach. In this …
Enhanced autism spectrum disorder facial expression recognition using hybrid weighed quantum particle swarm optimization with Fast Mask Recurrent Convolutional …
VS Devaraj, E Periyathambi - Traitement du Signal, 2024 - search.proquest.com
Abstract Autism Spectrum Disorder (ASD) affects brain development, impacting
socialization, communication, and creativity in children. Signs typically appear within the first …
socialization, communication, and creativity in children. Signs typically appear within the first …
BLSF: Adaptive Learning for Small-Sample Medical Data with Broad Learning System Forest Integration
The Broad Learning System Forest (BLSF) model proved to be the preeminent classifier
across all assessed datasets, demonstrating outstanding performance and efficiency. In the …
across all assessed datasets, demonstrating outstanding performance and efficiency. In the …
Revolutionizing Anemia Classification with Multilayer Extremely Randomized Tree Learning Machine for Unprecedented Accuracy.
Anemia is a prevalent global health issue that is characterized by a deficit in red blood cells
or low levels of hemoglobin. This condition is influenced by various causes, including …
or low levels of hemoglobin. This condition is influenced by various causes, including …
Multimodal Deep Learning in Early Autism Detection—Recent Advances and Challenges
SS Dcouto, J Pradeepkandhasamy - Engineering Proceedings, 2024 - mdpi.com
Autism spectrum disorder (ASD) is a global concern, with a prevalence rate of approximately
1 in 36 children according to estimates from the Centers for Disease Control and Prevention …
1 in 36 children according to estimates from the Centers for Disease Control and Prevention …
Evaluation of Stochastic Gradient Descent Optimizer on U-Net Architecture for Brain Tumor Segmentation
P Purwono, IS Mangkunegara - International Journal of Robotics …, 2023 - pubs2.ascee.org
A brain tumor is a type of disease that is quite dangerous in the world. This disease is one of
the main causes of human death and has a high risk of recurrence. There are several types …
the main causes of human death and has a high risk of recurrence. There are several types …
Voice Features Examination for Parkinson's Disease Detection Utilizing Machine Learning Methods
Manageable symptoms can be a critical and important thing for people with Parkinson's
disease (PWP) in order to maintaining their quality of life. PWP early detection and …
disease (PWP) in order to maintaining their quality of life. PWP early detection and …
[PDF][PDF] The Effectiveness of Data Imputations on Myocardial Infarction Complication Classification Using Machine Learning Approach with Hyperparameter Tuning
Complications from Myocardial Infarction (MI) represent a critical medical emergency
caused by the blockage of blood flow to the heart muscle, primarily due to a blood clot in a …
caused by the blockage of blood flow to the heart muscle, primarily due to a blood clot in a …