Latest research trends in fall detection and prevention using machine learning: A systematic review
Falls are unusual actions that cause a significant health risk among older people. The
growing percentage of people of old age requires urgent development of fall detection and …
growing percentage of people of old age requires urgent development of fall detection and …
Automated detection of sleep stages using deep learning techniques: A systematic review of the last decade (2010–2020)
Sleep is vital for one's general well-being, but it is often neglected, which has led to an
increase in sleep disorders worldwide. Indicators of sleep disorders, such as sleep …
increase in sleep disorders worldwide. Indicators of sleep disorders, such as sleep …
Classification of skin disease using deep learning neural networks with MobileNet V2 and LSTM
Deep learning models are efficient in learning the features that assist in understanding
complex patterns precisely. This study proposed a computerized process of classifying skin …
complex patterns precisely. This study proposed a computerized process of classifying skin …
[HTML][HTML] An ensemble approach for classification and prediction of diabetes mellitus using soft voting classifier
Diabetes is a dreadful disease identified by escalated levels of glucose in the blood.
Machine learning algorithms help in identification and prediction of diabetes at an early …
Machine learning algorithms help in identification and prediction of diabetes at an early …
A survey on deep learning in medicine: Why, how and when?
New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …
data, clinical images, genome sequences, data on prescribed therapies and results …
Machine learning based diabetes classification and prediction for healthcare applications
The remarkable advancements in biotechnology and public healthcare infrastructures have
led to a momentous production of critical and sensitive healthcare data. By applying …
led to a momentous production of critical and sensitive healthcare data. By applying …
Analysis of factors affecting IoT-based smart hospital design
Currently, rapidly developing digital technological innovations affect and change the
integrated information management processes of all sectors. The high efficiency of these …
integrated information management processes of all sectors. The high efficiency of these …
From bit to bedside: a practical framework for artificial intelligence product development in healthcare
Artificial intelligence (AI) in healthcare holds great potential to expand access to high‐quality
medical care, while reducing systemic costs. Despite hitting headlines regularly and many …
medical care, while reducing systemic costs. Despite hitting headlines regularly and many …
Automatic text summarization of biomedical text data: a systematic review
In recent years, the evolution of technology has led to an increase in text data obtained from
many sources. In the biomedical domain, text information has also evidenced this …
many sources. In the biomedical domain, text information has also evidenced this …
An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works
A Shoeibi, P Moridian, M Khodatars… - Computers in biology …, 2022 - Elsevier
Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …