Federated transfer learning for machinery fault diagnosis: A comprehensive review of technique and application

Q Qian, B Zhang, C Li, Y Mao, Y Qin - Mechanical Systems and Signal …, 2025 - Elsevier
As a crucial role in the prognostic and health management of mechanical equipment, fault
diagnosis encounters serious challenges, such as the scarcity of fault samples, the high cost …

Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review

M Jafari, A Shoeibi, M Khodatars, N Ghassemi… - Computers in Biology …, 2023 - Elsevier
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …

DSCC_Net: multi-classification deep learning models for diagnosing of skin cancer using dermoscopic images

M Tahir, A Naeem, H Malik, J Tanveer, RA Naqvi… - Cancers, 2023 - mdpi.com
Simple Summary This paper proposes a deep learning-based skin cancer classification
network (DSCC_Net) that is based on a convolutional neural network (CNN) and …

Hep-pred: hepatitis c staging prediction using fine gaussian svm

TM Ghazal - Computers, Materials & Continua, 2021 - research.skylineuniversity.ac.ae
Hepatitis C is a contagious blood-borne infection, and it is mostly asymptomatic during the
initial stages. Therefore, it is difficult to diagnose and treat patients in the early stages of …

CDC_Net: Multi-classification convolutional neural network model for detection of COVID-19, pneumothorax, pneumonia, lung Cancer, and tuberculosis using chest X …

H Malik, T Anees, M Din, A Naeem - Multimedia Tools and Applications, 2023 - Springer
Abstract Coronavirus (COVID-19) has adversely harmed the healthcare system and
economy throughout the world. COVID-19 has similar symptoms as other chest disorders …

Blockchain technology in healthcare: A systematic review

H Saeed, H Malik, U Bashir, A Ahmad, S Riaz, M Ilyas… - Plos one, 2022 - journals.plos.org
Blockchain technology (BCT) has emerged in the last decade and added a lot of interest in
the healthcare sector. The purpose of this systematic literature review (SLR) is to explore the …

A comprehensive analysis of recent deep and federated-learning-based methodologies for brain tumor diagnosis

A Naeem, T Anees, RA Naqvi, WK Loh - Journal of Personalized …, 2022 - mdpi.com
Brain tumors are a deadly disease with a high mortality rate. Early diagnosis of brain tumors
improves treatment, which results in a better survival rate for patients. Artificial intelligence …

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

K Lekadir, A Feragen, AJ Fofanah, AF Frangi… - arxiv preprint arxiv …, 2023 - arxiv.org
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the
deployment and adoption of AI technologies remain limited in real-world clinical practice. In …

[HTML][HTML] Towards automated eye cancer classification via VGG and ResNet networks using transfer learning

DF Santos-Bustos, BM Nguyen, HE Espitia - Engineering Science and …, 2022 - Elsevier
Complex tasks such as disease diagnosis or semantic segmentation are now becoming
easier to tackle in part due to increasing advances in computing and storage. This study …

Untangling computer-aided diagnostic system for screening diabetic retinopathy based on deep learning techniques

MS Farooq, A Arooj, R Alroobaea, AM Baqasah… - Sensors, 2022 - mdpi.com
Diabetic Retinopathy (DR) is a predominant cause of visual impairment and loss.
Approximately 285 million worldwide population is affected with diabetes, and one-third of …