Article
Health Care Sciences & Services
Hasnae Zerouaoui, Ali Idri
Summary: Breast cancer is the leading cause of death among women worldwide. Medical image analysis using Machine Learning and Image Processing techniques is a promising area of research for the diagnosis and decision-making of BC. This review found that Deep Learning techniques were commonly used for classification in the analysis of Mamograms for BC imaging.
JOURNAL OF MEDICAL SYSTEMS
(2021)
Article
Public, Environmental & Occupational Health
Min Lu, Xuehui Wang, Kaijun Shen, Chengpeng Ji, Wenxia Li
Summary: The study aimed to examine gender differences in disability-free life expectancy (DFLE) and DFLE/LE ratio among older adults in China, and to explore the changing trends from 2010 to 2020, as well as the implications for public policies. Mortality data and disability rate data from the Sixth and Seventh China Population Census were used to estimate LE, DFLE, and DFLE/LE ratio by gender. Results showed that from 2010 to 2020, both male and female older adults in China experienced an increase in DFLE along with life expectancy. However, there remained a gender difference in DFLE/LE ratio, particularly among the oldest old age group (age 80 and above), with female older adults having a lower ratio compared to male.
FRONTIERS IN PUBLIC HEALTH
(2023)
Article
Medicine, General & Internal
Holly Q. Bennett, Andrew Kingston, Ilianna Lourida, Louise Robinson, Lynne Corner, Carol E. G. Brayne, Fiona E. Matthews, Carol Jagger
Summary: Disability-free life expectancy inequalities between different socioeconomic statuses are widening, not solely due to the presence of multiple long-term conditions (MLTCs). Reduced disability incidence with MLTCs was only achieved in the most affluent populations, with DFLE inequalities still existing in people without MLTCs.
Article
Multidisciplinary Sciences
Gonzalo Mena, Pamela P. Martinez, Ayesha S. Mahmud, Pablo A. Marquet, Caroline O. Buckee, Mauricio Santillana
Summary: The COVID-19 pandemic has disproportionately impacted cities, with a strong association found between socioeconomic status and both disease incidence and mortality. People in lower socioeconomic municipalities were less likely to adhere to lockdown measures and faced higher testing delays and positivity rates. This highlights the critical consequences of socioeconomic inequalities on health outcomes.
Article
Computer Science, Information Systems
Mohamed Benbouzid, Tarek Berghout
Summary: Data-driven prognostics and health management play a crucial role in improving the productivity of industrial processes by enabling accurate maintenance planning. The increasing complexity of systems and cyber-physical connectivity have posed numerous challenges, which now include decentralized learning challenges. This perspective paper describes these challenges and provides future directions based on a comprehensive state-of-the-art review.
Article
Public, Environmental & Occupational Health
Lijun Chen, Lu Wang, Yun Qian, Hai Chen
Summary: This study investigates the contributions of sex, age, and cause-specific factors to changes in life expectancy and health-adjusted life expectancy in China from 1990 to 2019. The results show that noncommunicable diseases have played a major role in the increase of life expectancy. However, HIV/AIDS, lung cancer, ischemic heart disease, and other diseases have had negative effects on life expectancy, and targeted interventions are needed to reduce their impact. The study also emphasizes the importance of addressing disparities in mortality and disability among different sexes and age groups.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Public, Environmental & Occupational Health
Masahiro Nishi, Reo Nagamitsu, Satoaki Matoba
Summary: This study aims to develop a prediction model for healthy life years without activity limitations and apply it in a health policy to prolong healthy life years. The model showed high performance and wide utility by using machine learning on the data from the Comprehensive Survey of Living Conditions in Japan.
JMIR PUBLIC HEALTH AND SURVEILLANCE
(2023)
Article
Computer Science, Information Systems
Yao Yu, Jie Ma, Weidong Zhao, Zhenmin Li, Shuai Ding
Summary: The study introduced a dataset containing multi-state colposcopy images and proposed a new computer-aided method for cervical cancer screening. The dataset was comprehensively evaluated using various methods, and a CIN grading model based on the MSCI dataset was established, showing high classification performance.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2021)
Article
Cardiac & Cardiovascular Systems
Hao Ma, Xuan Wang, Qiaochu Xue, Xiang Li, Zhaoxia Liang, Yoriko Heianza, Oscar H. Franco, Lu Qi
Summary: Adhering to a high CVH, as defined by the LE8 score, is associated with a significantly increased life expectancy in US adults. However, more research needs to be conducted in other races and ethnicities to further explore this association.
Article
Public, Environmental & Occupational Health
J. Currie, T. Boyce, L. Evans, M. Luker, S. Senior, M. Hartt, S. Cottrell, N. Lester, D. Huws, C. Humphreys, K. Little, V Adekanmbi, S. Paranjothy
Summary: The study analyzed the trends and factors contributing to life expectancy inequalities between different social groups in Wales, highlighting significant disparities in different gender and age groups as well as causes of death. The results revealed that inequalities persist and are worsening, particularly among women, emphasizing the need for further attention and potential interventions to address these disparities.
Article
Public, Environmental & Occupational Health
Holly Q. Bennett, Andrew Kingston, Gemma Spiers, Louise Robinson, Lynne Corner, Clare Bambra, Carol Brayne, Fiona E. Matthews, Carol Jagger
Summary: The study found that over the past 20 years, gains in DFLE at age 65 were greatest for the most advantaged men and women. The most advantaged women had a reduced risk of incident disability, while the most advantaged men had a greater likelihood of recovery and reduced disability-free mortality risk.
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
(2021)
Article
Multidisciplinary Sciences
Thomas Bryan Smith, Raffaele Vacca, Luca Mantegazza, Ilaria Capua
Summary: The United Nations' Sustainable Development Goals are diverse and interdependent, consisting of 169 targets and 231 indicators covering various areas such as health, environment, and human rights. An alternative approach is presented in the study to quantify the complex network of SDG interdependencies using computational methods, revealing a strong discursive divide between environmental goals and other SDGs, as well as unexpected interdependencies between goals in different areas. While some alignment is found between UN discourse and integration patterns in SDG-related science, significant differences also exist between priorities in UN discourse and global scientific discourse.
SCIENTIFIC REPORTS
(2021)
Article
Mechanics
Haipeng Song, Jing Liu, Hao Zhang, Juan Du
Summary: This paper investigates the fatigue failure behavior of pre-corroded Al-Li alloy 2050-T8 and develops a data-driven fatigue life prediction model based on machine learning. The experimental results show that the initiation of fatigue macro-cracks due to corrosion pits varies with the corrosion morphology. Four forms of fatigue micro-crack initiation are summarized. The proposed data-driven model effectively predicts the fatigue life of pre-corroded aluminum alloy with high accuracy.
ENGINEERING FRACTURE MECHANICS
(2023)
Article
Multidisciplinary Sciences
Lorenzo Rocco, Elena Fumagalli, Andrew J. Mirelman, Marc Suhrcke
Summary: According to the study, reducing mortality and disability adjusted life years (DALYs) can promote per capita GDP growth. The effects are moderate, but significant, and are similar for both mortality and DALYs.
Article
Geriatrics & Gerontology
Maya Yamato, Sanae Matsuyama, Yoshitaka Murakami, Jun Aida, Yukai Lu, Yumi Sugawara, Ichiro Tsuji
Summary: Tooth loss has been linked to a shorter disability-free life expectancy, but practicing oral self-care, such as brushing teeth regularly and using dentures, can increase disability-free life expectancy in older individuals with tooth loss.
Article
Computer Science, Artificial Intelligence
Alishba Adeel, Muhammad Attique Khan, Tallha Akram, Abida Sharif, Mussarat Yasmin, Tanzila Saba, Kashif Javed
Summary: Agriculture is crucial for many countries, but faces challenges such as climate changes and diseases. This article presents a machine learning solution for early identification of grape diseases, utilizing a combination of deep learning and traditional methods to achieve 99% accuracy.
Article
Computer Science, Information Systems
Tanzila Saba
Summary: Violence is a critical social problem that needs to be evaluated using computer vision approaches. This research proposes a lightweight computational architecture for classifying violent and non-violent activities. A deep learning model is employed to detect violent actions and assist in real-time exposure of such activities.
JOURNAL OF INFORMATION SCIENCE
(2023)
Article
Computer Science, Software Engineering
Amjad Rehman Khan, Tanzila Saba, Muhammad Zeeshan Khan, Suliman Mohamed Fati, Muhammad Usman Ghani Khan
Summary: This research aims to solve the problem of automated behavior analysis in examinations by automatically identifying and distinguishing cheating examinees based on their activities. Ensemble learning and deep learning-based algorithms are used to monitor suspicious head movements and prohibited objects, and the intersection over union method is used to detect the interactive use of prohibited objects. The experimental results demonstrate that this method achieves state-of-the-art performance in automated examinee invigilation.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Computer Science, Information Systems
Tanzila Saba, Amjad Rehman, Tariq Sadad, Zahid Mehmood
Summary: This article discusses the significance of image tempering in the modern era and the concerns over data integrity. It emphasizes on the importance of detecting image anomalies through artificial intelligence techniques. The authors propose a custom convolutional neural network (CNN) architecture with a pre-trained model ResNet101 using a transfer learning approach. The model is trained and evaluated on different datasets, achieving a high accuracy of 98.4% using the Coverage dataset.
JOURNAL OF INFORMATION SCIENCE
(2023)
Article
Automation & Control Systems
Khalid Haseeb, Amjad Rehman, Tanzila Saba, Saeed Ali Bahaj, Huihui Wang, Houbing Song
Summary: This paper presents an efficient and trusted autonomous vehicle routing protocol using 6G networks, aiming to guarantee high quality of service and data coverage. The proposed protocol establishes a routing process using a simulated annealing optimization technique and statistically guarantees the optimal solution. It also provides a risk-aware security system through reliable session-oriented communication with network edges, avoiding uncertainties in the autonomous system. Simulations verify the effectiveness of the proposed protocol in constructing a green communication system with authenticity and system intelligence.
Article
Computer Science, Information Systems
Tanzila Saba, Amjad Rehman, Khalid Haseeb, Teg Alam, Gwanggil Jeon
Summary: Rapid growth of the Internet and cloud services plays a vital role in smart application development. However, edge computing faces challenges in data aggregation and security. This research proposes a distributed load balancing protocol using particle swarm optimization to reduce response time and ensure network integrity.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Jaber Alyami, Amjad Rehman, Fahad Almutairi, Abdul Muiz Fayyaz, Sudipta Roy, Tanzila Saba, Alhassan Alkhurim
Summary: Early diagnosis of brain tumors is crucial for treatment planning and increasing patient survival rates. Manual diagnosis is difficult and prone to error, necessitating an automated brain tumor detection system. This research presents an efficient deep learning-based system using a deep convolutional network and salp swarm algorithm for brain tumor classification from MRI images. Preprocessing and data augmentation techniques are employed to enhance classification rate, and feature selection techniques are used to achieve optimal tumor classification accuracy.
COGNITIVE COMPUTATION
(2023)
Article
Computer Science, Information Systems
Deep R. Kothadiya, Chintan M. Bhatt, Tanzila Saba, Amjad Rehman, Saeed Ali Bahaj
Summary: Sign language is commonly used by the hearing impaired for communication. Recognizing signs is crucial for bridging the communication gap with these individuals. This paper proposes the use of Transformer Encoder as an effective tool for sign language recognition, achieving satisfactory accuracy with minimal training epochs.
Article
Computer Science, Information Systems
Muhammad Irfan, Tariq Shah, Ghazanfar Farooq Siddiqui, Amjad Rehman, Tanzila Saba, Saeed Ali Bahaj
Summary: S-box is a crucial component in modern symmetric ciphering techniques, which enhances randomness and confidentiality in symmetric encryption. This article proposes a robust method for constructing S-boxes based on Gravesian octonion integers. The strength of the newly generated S-box is evaluated through rigorous security analysis and compared with existing schemes, showing high resistance against various cryptanalysis attacks.
Article
Oncology
Zubaira Naz, Muhammad Usman Ghani Khan, Tanzila Saba, Amjad Rehman, Haitham Nobanee, Saeed Ali Bahaj
Summary: This research provides an explanation of the classification results of different lung pulmonary diseases so that doctors can understand the reason that causes these diseases. The use of explainable artificial intelligence helps with automatic disease diagnosis and treatment.
Article
Health Care Sciences & Services
Sarah Zuhair Kurdi, Mohammed Hasan Ali, Mustafa Musa Jaber, Tanzila Saba, Amjad Rehman, Robertas Damasevicius
Summary: The field of medical image processing is important for brain tumor classification and early diagnosis. This study proposes the use of the Harris Hawks optimized convolution network (HHOCNN) to improve the efficiency of existing systems in identifying tumor regions and hidden edge details. The proposed system achieved a tumor recognition accuracy of 98% on the Kaggle dataset.
JOURNAL OF PERSONALIZED MEDICINE
(2023)
Article
Computer Science, Interdisciplinary Applications
Shahzada Daud, Muti Ullah, Amjad Rehman, Tanzila Saba, Robertas Damasevicius, Abdul Sattar
Summary: This study utilized machine learning techniques to categorize online news articles and proposed the hyperparameter-optimized SVM method. Additionally, five other ML techniques were optimized and compared. The results showed that the optimized SVM model performed the best.
Article
Computer Science, Information Systems
Amjad Rehman, Tanzila Saba, Muhammad Mujahid, Faten S. Alamri, Narmine ElHakim
Summary: Parkinson's disease is a prevalent neurological disorder that poses a challenging task in early detection due to a shortage of trained neurologists. This study collected voice data from Parkinson's disease patients to investigate the diagnostic significance of speech abnormalities. By addressing the issue of imbalanced datasets using sampling techniques, a hybrid model achieved high accuracy, precision, recall, and f1 score in detecting Parkinson's disease.
Article
Medicine, General & Internal
Muhammad Mujahid, Amjad Rehman, Teg Alam, Faten S. Alamri, Suliman Mohamed Fati, Tanzila Saba
Summary: Alzheimer's disease is an incurable neurological disorder that leads to a gradual decline in cognitive abilities. Early detection and accurate diagnosis can significantly mitigate symptoms. Deep learning, with its automatic feature extraction and optimized training process, provides a promising approach for diagnosing the disease.
Article
Multidisciplinary Sciences
Muhammad Attique Khan, Yu-Dong Zhang, Majed Alhusseni, Seifedine Kadry, Shui-Hua Wang, Tanzila Saba, Tassawar Iqbal
Summary: In this paper, a method for action recognition based on the fusion of shape and deep learning features is proposed. The method consists of two steps: human extraction and action recognition. By combining entropy-controlled feature selection and parallel conditional entropy approach, the features are fused and classified, achieving a high accuracy rate.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Public, Environmental & Occupational Health
Rodrigo C. Menezes, Isabella B. B. Ferreira, Luciana Sobral, Stefania L. Garcia, Hugo N. Pustilnik, Mariana Araujo-Pereira, Bruno B. Andrade
Summary: This study aimed to identify the clinical features associated with viral pathogens responsible for severe lower respiratory tract infections (LRTI) in children. The study found that different viral agents have distinct associations with clinical features in children.
JOURNAL OF INFECTION AND PUBLIC HEALTH
(2024)
Article
Public, Environmental & Occupational Health
Ambrina Khatoon, Syed F. Hussain, Syed M. Shahid, Santosh Kumar Sidhwani, Salman Ahmed Khan, Omer Ahmed Shaikh, Abdulqadir J. Nashwan
Summary: Despite the increasing incidence of Staphylococcus aureus infection and dissemination in Pakistan, research on the epidemiology of different Staphylococcus aureus clones has been limited. This study used multilocus sequence typing (MLST) to analyze the epidemiology of Staphylococcus aureus in the area, finding high diversity of locally circulating clones defined by their geographic epidemiology.
JOURNAL OF INFECTION AND PUBLIC HEALTH
(2024)
Review
Public, Environmental & Occupational Health
Amir Khorram-Manesh, Krzysztof Goniewicz, Frederick M. Burkle Jr
Summary: This article discusses the management approach for globalized diseases in a globalized world. Through literature review and analysis, key focuses including data-driven decision-making, robust technology infrastructure, global cooperation, and ongoing public health education are identified. The weaknesses of current pandemic management systems are revealed, and recommendations for strengthening future pandemic management are provided.
JOURNAL OF INFECTION AND PUBLIC HEALTH
(2024)
Article
Public, Environmental & Occupational Health
Mst S. Munira, Yuta Okada, Hiroshi Nishiura
Summary: This study estimates the life expectancy at birth in Japan at the end of 2022 using death datasets from Aichi and Fukui prefectures. The results suggest that the impact of the pandemic on life expectancy was relatively small by the end of 2022.
JOURNAL OF INFECTION AND PUBLIC HEALTH
(2024)
