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Article
Genetics & Heredity
Ali Raza et al.
Summary: This study focuses on predicting genetic disorders using artificial intelligence-based methods. It proposes a novel feature engineering approach and classifier chain approach, and evaluates the performance using multiple evaluation metrics. Results show that extreme gradient boosting (XGB) outperforms state-of-the-art approaches in terms of both performance and computational complexity.
Article
Computer Science, Artificial Intelligence
Disha Deotale et al.
Summary: This study focuses on physiotherapy video dataset and proposes a deep learning-based neural network framework to address the issues in continuous human activity recognition.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
Ali Raza et al.
Summary: Microbe organisms make up a significant portion of the earth's living matter, and they also inhabit the human body. These microbes pose health threats and can lead to various diseases in humans. This study aims to predict microbe organisms in the human body through an automated approach. A novel hybrid microbes classifier (HMC) based on decision tree and extra tree classifiers using voting criteria is proposed. The HMC approach achieves high accuracy, geometric mean score, precision score, and Cohen Kappa score, outperforming existing models. The research helps microbiologists accurately identify microbe organisms and prevent diseases through early detection.
Article
Engineering, Multidisciplinary
Ali Raza et al.
Summary: Kinematic motion detection aims to identify a person's actions based on activity data. This research has important applications in health care, such as health monitoring, preventing obesity, virtual reality, and assisting workers and the elderly. The study utilizes smartphone sensor data and explores valuable patterns and insights. The proposed ensemble learning-based ERD method outperforms other studies with high accuracy.
Article
Computer Science, Information Systems
Armin Danesh Pazho et al.
IEEE Internet of Things Journal
(2023)
Article
Computer Science, Information Systems
Ali Raza et al.
Summary: Network attacks exploit computer network vulnerabilities, causing security threats and financial losses. Organizations can use machine learning techniques to enhance the accuracy and efficiency of detecting network attacks.
Article
Computer Science, Information Systems
Ali Raza et al.
Summary: Gunshot sounds are common in crimes and can cause fear and psychological trauma to victims. This study proposes an efficient approach for detecting gunshot sounds, which can provide key information for criminal investigations and help prevent crimes.
Article
Multidisciplinary Sciences
Masami Yokogawa et al.
Summary: This study explores how physiotherapists engage with older adults with dementia to encourage exercise and participation in physical activity. The findings reveal that physiotherapists engage with dementia patients by making structured preparations, linking exercise therapy to daily life, discovering changes, assessing cognitive function, and accommodating individual differences. These findings can help physiotherapists encourage dementia patients to participate in physical therapy and benefit from exercise.
Article
Multidisciplinary Sciences
Anitha Rani Inturi et al.
Summary: Human activity recognition is important for various applications, and now it can also be used for fall detection systems for assisting older people. Our paper presents a vision-based solution for fall detection, analyzing human joint points and using neural networks.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Chemistry, Analytical
Imran Ullah Khan et al.
Summary: In recent years, Human Activity Recognition (HAR) has become an important research topic in the domains of health and human-machine interaction. Existing AI-based models for activity recognition show poor performance on long-term HAR due to their inability to extract spatial and temporal features. Additionally, there is a limited availability of publicly accessible datasets for physical activities recognition. To address these challenges, a hybrid model incorporating Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) is developed, achieving an accuracy of 90.89% on a new challenging dataset containing 12 different classes of human physical activities. This demonstrates the suitability of the proposed model for HAR applications.
Article
Environmental Sciences
Saeed Alqadhi et al.
Summary: The study constructed four optimized ensemble machine learning algorithms for landslide susceptibility mapping, with the PSO-ANN model identified as the best model and the LR model-based hybrid ensemble machine learning model performing better than the PSO-ANN model. Various resources were declared as landslide risk zones, and elevation, soil-texture, slope, rainfall, and road distance were considered the most sensitive parameters for landslide occurrences.
GEOCARTO INTERNATIONAL
(2022)
Article
Computer Science, Artificial Intelligence
BeomJun Jo et al.
Summary: Pose estimation is a significant strategy that has been actively researched in various fields. This paper compares and analyzes four popular pose estimation models using pre-classified images.
TRAITEMENT DU SIGNAL
(2022)
Article
Multidisciplinary Sciences
Ali Raza et al.
Summary: Maternal health is crucial for women during pregnancy and the postpartum period. This study aims to develop an artificial neural network-based system for predicting maternal health risks using health data records. The proposed deep neural network architecture, DT-BiLTCN, achieves high accuracy results with the support vector machine on a dataset of 1218 samples. The analysis identifies blood pressure, heart rate, and age as the strongest indicators of maternal health risks during pregnancy.
Article
Biophysics
Lucas D. Haberkamp et al.
Summary: This study investigated the validity of 2D pose estimation models for evaluating kinematics in adolescent athletes. The results showed significant differences between 2D pose estimation and 3D motion analysis in sagittal and frontal plane angles during single-leg squats, but moderate to strong correlations were observed between the two techniques in most cases.
JOURNAL OF BIOMECHANICS
(2022)
Article
Chemistry, Multidisciplinary
Ali Raza et al.
Summary: Asteroseismology uses solar-type oscillations to study the physical structure of stars, and a recent study applies deep learning to classify RGB and HeB. The formation of HeB is found to be related to the values of features Numax and Epsilon, based on the analysis of frequency separation and oscillation power frequency.
APPLIED SCIENCES-BASEL
(2022)
Article
Health Care Sciences & Services
Rawad Abdulghafor et al.
Summary: In recent decades, epidemic and pandemic illnesses have become increasingly common. Smart technology is widely used in medical applications, and the automated detection of symptoms through studying body language has become a significant research area. However, there is still a lack of comprehensive studies on this topic. This literature review examines past papers that utilized AI for body language classification and provides an overview of different methods proposed and their significance.
Article
Computer Science, Information Systems
Juan Jesus Ojeda-Castelo et al.
Summary: Gesture recognition is an ideal means of interaction that allows users to avoid contact with surfaces, making it safe and hygienic. Despite being researched for many years, it has not replaced keyboards and mice. Deep learning has made significant advancements in gesture recognition, offering the potential for it to become a viable option for daily user interaction.
Article
Computer Science, Information Systems
Kai-Chih Lin et al.
Summary: This study aims to propose an artificial intelligence Internet of Things program for fall prevention and improve mobility in older adults by implementing the Asian Working Group for Sarcopenia criteria, which showed promising results in increasing gait speed and reducing fall risk after 3 months of field practice.
Article
Construction & Building Technology
Han Luo et al.
AUTOMATION IN CONSTRUCTION
(2020)
Article
Chemistry, Multidisciplinary
Yeong-Hyeon Byeon et al.
APPLIED SCIENCES-BASEL
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Junbang Liang et al.
2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2019)
(2019)
Article
Computer Science, Information Systems
Wenming Cao et al.
Article
Automation & Control Systems
Congqi Cao et al.
IEEE TRANSACTIONS ON CYBERNETICS
(2018)
Article
Hematology
K. Wittmeier et al.
