Adaptive dense bidirectional-based recurrent neural network with exponential soft ratio loss function for analyzing the virtual reality experiences using AI-based deep features

A deep learning model using convolutional neural networks and conditional generative adversarial networks with multi-head attention for stock prediction

Zhiqi Wang, Feng Gu

Stock prediction utilizing machine learning and deep learning models has attracted increasing attention in recent years. While recent research has made substantial progress in stock forecasting, many existing models perform inconsistently across markets and are sensitive to rando…Read more

Systematic review of unveiling the potential of AI using machine learning and deep learning methods in neurodegenerative diseases

S. Mohanraj, Sujatha Radhakrishnan

Background Neurodegenerative diseases (NDDs) are becoming a major worldwide issue, especially for the elderly because they are incurable and permanent. It is extremely difficult to provide any medication to people suffering from NDDs. Comprehending essential processes of NDDs are…Read more

A review of current imaging techniques for histopathology-based breast cancer diagnosis with comparative insights using machine learning and deep learning models and its challenges and future directions

Gokula Lakshmi G., Uma Kuppusamy

Breast cancer remains one of the principal reasons of death among women worldwide, highlighting the critical requirement for primary and exact diagnosis to expand patient persistence rates. Manual clarification of histopathological slides is frequently subjective, time-consuming,…Read more

BrainNet: a custom-designed CNN and transfer learning-based models for diagnosing brain tumors from MRI images

Adil H. Khan, Asad Khan, D. N. F. Awang Iskandar, Hiren Mewada, Saqib Saeed, Fahad Algarni, et al.

Cancer remains the second leading cause of death globally, with brain tumors exhibiting some of the lowest survival rates among all cancer types. Accurate diagnosis, guided by the tumor’s structure and location, is essential for selecting appropriate treatment strategies and impr…Read more

Also available via: PeerJ, Inc.

A novel approach for yoga pose estimation based on in-depth analysis of human body joint detection accuracy

Miral Desai, Hiren Mewada

Virtual motion and pose from images and video can be estimated by detecting body joints and their interconnection. The human body has diverse and complicated poses in yoga, making its classification challenging. This study estimates yoga poses from the images using a neural netwo…Read more

Also available via: PeerJ, Inc.

Partially adaptive optimization driven spatial focused CNN with Gompertz non-linearity for interpretable Alzheimer’s disease diagnosis

Muhammad Waqar, Zeshan Aslam Khan, Mirza Hashim Ali Baig, Chung-Chian Hsu, Ihsan Ul Haq, Saadia Khan, et al.

Recently, deep learning has revolutionized various scientific disciplines. Strategies based on deep learning have consistently surpassed traditional methods, proving extraordinary efficiency in the healthcare environment. Alzheimer’s disease is one of the major global health thre…Read more