Machine learning for dementia prediction: a systematic review and future research directions

A Javeed, AL Dallora, JS Berglund, A Ali, L Ali… - Journal of medical …, 2023 - Springer
Abstract Nowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully
provided automated solutions to numerous real-world problems. Healthcare is one of the …

Applications of machine learning predictive models in the chronic disease diagnosis

G Battineni, GG Sagaro, N Chinatalapudi… - Journal of personalized …, 2020 - mdpi.com
This paper reviews applications of machine learning (ML) predictive models in the diagnosis
of chronic diseases. Chronic diseases (CDs) are responsible for a major portion of global …

Accelerating materials discovery using machine learning

Y Juan, Y Dai, Y Yang, J Zhang - Journal of Materials Science & …, 2021 - Elsevier
The discovery of new materials is one of the driving forces to promote the development of
modern society and technology innovation, the traditional materials research mainly …

An MRI scans-based Alzheimer's disease detection via convolutional neural network and transfer learning

KT Chui, BB Gupta, W Alhalabi, FS Alzahrani - Diagnostics, 2022 - mdpi.com
Alzheimer's disease (AD) is the most common type (> 60%) of dementia and can wreak
havoc on the psychological and physiological development of sufferers and their carers, as …

Automatic and non-invasive Parkinson's disease diagnosis and severity rating using LSTM network

E Balaji, D Brindha, VK Elumalai, R Vikrama - Applied Soft Computing, 2021 - Elsevier
Deep learning has a huge potential in healthcare for uncovering the hidden patterns from
large volume of clinical data to diagnose different diseases. This paper presents a novel …

Early detection of cognitive decline using machine learning algorithm and cognitive ability test

A Revathi, R Kaladevi, K Ramana… - Security and …, 2022 - Wiley Online Library
Elderly people are the assets of the country and the government can ensure their peaceful
and healthier life. Life expectancy of individuals has expanded with technological …

A systematic review on AI/ML approaches against COVID-19 outbreak

O Dogan, S Tiwari, MA Jabbar, S Guggari - Complex & Intelligent Systems, 2021 - Springer
Abstract A pandemic disease, COVID-19, has caused trouble worldwide by infecting millions
of people. The studies that apply artificial intelligence (AI) and machine learning (ML) …

Analyzing chronic disease biomarkers using electrochemical sensors and artificial neural networks

K Sinha, Z Uddin, HI Kawsar, S Islam, MJ Deen… - TrAC Trends in …, 2023 - Elsevier
Chronic diseases are persistent health conditions that affect our quality of life, increase
morbidity and mortality, and are a global challenge. Further, the increasing prevalence of …

Automated detection of construction work at heights and deployment of safety hooks using IMU with a barometer

H Choo, B Lee, H Kim, B Choi - Automation in Construction, 2023 - Elsevier
An automated system that identifies work at height and the fastening state of safety hooks
using wearable sensors was developed to prevent falls from height (FFH). This system …

Robust Classification and Detection of Big Medical Data Using Advanced Parallel K-Means Clustering, YOLOv4, and Logistic Regression

FH Awad, MM Hamad, L Alzubaidi - Life, 2023 - mdpi.com
Big-medical-data classification and image detection are crucial tasks in the field of
healthcare, as they can assist with diagnosis, treatment planning, and disease monitoring …