A comprehensive review on federated learning based models for healthcare applications

S Sharma, K Guleria - Artificial Intelligence in Medicine, 2023 - Elsevier
A disease is an abnormal condition that negatively impacts the functioning of the human
body. Pathology determines the causes behind the disease and identifies its development …

A review of medical federated learning: Applications in oncology and cancer research

A Chowdhury, H Kassem, N Padoy, R Umeton… - International MICCAI …, 2021 - Springer
Abstract Machine learning has revolutionized every facet of human life, while also becoming
more accessible and ubiquitous. Its prevalence has had a powerful impact in healthcare …

The brain tumor segmentation (BRATS) challenge 2023: Focus on pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

AF Kazerooni, N Khalili, X Liu, D Haldar, Z Jiang… - arXiv preprint arXiv …, 2023 - arxiv.org
Pediatric tumors of the central nervous system are the most common cause of cancer-related
death in children. The five-year survival rate for high-grade gliomas in children is less than …

[HTML][HTML] The brain tumor segmentation (brats) challenge 2023: glioma segmentation in sub-saharan Africa patient population (brats-africa)

M Adewole, JD Rudie, A Gbdamosi, O Toyobo… - ArXiv, 2023 - ncbi.nlm.nih.gov
Gliomas are the most common type of primary brain tumors. Although gliomas are relatively
rare, they are among the deadliest types of cancer, with a survival rate of less than 2 years …

Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions

W Lotter, MJ Hassett, N Schultz, KL Kehl, EM Van Allen… - Cancer Discovery, 2024 - AACR
Artificial intelligence (AI) in oncology is advancing beyond algorithm development to
integration into clinical practice. This review describes the current state of the field, with a …

Developing medical imaging AI for emerging infectious diseases

SC Huang, AS Chaudhari, CP Langlotz, N Shah… - nature …, 2022 - nature.com
Advances in artificial intelligence (AI) and computer vision hold great promise for assisting
medical staff, optimizing healthcare workflow, and improving patient outcomes. The COVID …

GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows

S Pati, SP Thakur, İE Hamamcı, U Baid… - Communications …, 2023 - nature.com
Deep Learning (DL) has the potential to optimize machine learning in both the scientific and
clinical communities. However, greater expertise is required to develop DL algorithms, and …

Current status and future directions: The application of artificial intelligence/machine learning for precision medicine

K Naik, RK Goyal, L Foschini, CW Chak… - Clinical …, 2024 - Wiley Online Library
Technological innovations, such as artificial intelligence (AI) and machine learning (ML),
have the potential to expedite the goal of precision medicine, especially when combined …

Automated federated pipeline for parameter-efficient fine-tuning of large language models

Z Fang, Z Lin, Z Chen, X Chen, Y Gao… - arXiv preprint arXiv …, 2024 - arxiv.org
Recently, there has been a surge in the development of advanced intelligent generative
content (AIGC), especially large language models (LLMs). However, for many downstream …

Exploring huntington's disease diagnosis via artificial intelligence models: a comprehensive review

S Ganesh, T Chithambaram, NR Krishnan, DR Vincent… - Diagnostics, 2023 - mdpi.com
Huntington's Disease (HD) is a devastating neurodegenerative disorder characterized by
progressive motor dysfunction, cognitive impairment, and psychiatric symptoms. The early …