Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives

U Raghavendra, A Gudigar, A Paul, TS Goutham… - Computers in Biology …, 2023 - Elsevier
A brain tumor is an abnormal mass of tissue located inside the skull. In addition to putting
pressure on the healthy parts of the brain, it can lead to significant health problems …

Multiple sclerosis diagnosis using machine learning and deep learning: challenges and opportunities

N Aslam, IU Khan, A Bashamakh, FA Alghool… - Sensors, 2022 - mdpi.com
Multiple Sclerosis (MS) is a disease that impacts the central nervous system (CNS), which
can lead to brain, spinal cord, and optic nerve problems. A total of 2.8 million are estimated …

Machine learning empowering personalized medicine: A comprehensive review of medical image analysis methods

I Galić, M Habijan, H Leventić, K Romić - Electronics, 2023 - mdpi.com
Artificial intelligence (AI) advancements, especially deep learning, have significantly
improved medical image processing and analysis in various tasks such as disease …

Application of entropy for automated detection of neurological disorders with electroencephalogram signals: a review of the last decade (2012-2022)

SJJ Jui, RC Deo, PD Barua, A Devi, J Soar… - IEEE …, 2023 - ieeexplore.ieee.org
An automated Neurological Disorder detection system can be considered as a cost-effective
and resource efficient tool for medical and healthcare applications. In automated …

Unlocking the potential of XAI for improved alzheimer's disease detection and classification using a ViT-GRU model

SM Mahim, MS Ali, MO Hasan, AAN Nafi, A Sadat… - IEEE …, 2024 - ieeexplore.ieee.org
Alzheimer's Disease (AD) is a significant cause of dementia worldwide, and its progression
from mild to severe affects an individual's ability to perform daily activities independently …

Artificial intelligence and neuroscience: An update on fascinating relationships

N Gopinath - Process Biochemistry, 2023 - Elsevier
Innovative technologies such as Artificial Intelligence (AI), deep learning, Machine learning
and optogenetics have been considered key components in the contribution to the …

A new one-dimensional testosterone pattern-based EEG sentence classification method

T Keles, AM Yildiz, PD Barua, S Dogan… - … Applications of Artificial …, 2023 - Elsevier
Electroencephalography (EEG) signals are crucial data to understand brain activities. Thus,
many papers have been proposed about EEG signals. In particular, machine learning …

Brain organoids: a game-changer for drug testing

C Giorgi, G Lombardozzi, F Ammannito, MS Scenna… - Pharmaceutics, 2024 - mdpi.com
Neurological disorders are the second cause of death and the leading cause of disability
worldwide. Unfortunately, no cure exists for these disorders, but the actual therapies are only …

Role of autophagy and proteostasis in neurodegenerative diseases: Exploring the therapeutic interventions

S Panwar, P Uniyal, N Kukreti, A Hashmi… - Chemical Biology & …, 2024 - Wiley Online Library
Neurodegenerative disorders are devastating disorders characterized by gradual loss of
neurons and cognition or mobility impairment. The common pathological features of these …

Voice pathology detection using optimized convolutional neural networks and explainable artificial intelligence-based analysis

R Jegan, R Jayagowri - Computer Methods in Biomechanics and …, 2024 - Taylor & Francis
This article proposes a noninvasive computer-aided assessment approach based on
optimized convolutional neural network for healthy and pathological voice detection. Firstly …