[HTML][HTML] Privacy-preserving artificial intelligence in healthcare: Techniques and applications

N Khalid, A Qayyum, M Bilal, A Al-Fuqaha… - Computers in Biology and …, 2023 - Elsevier
There has been an increasing interest in translating artificial intelligence (AI) research into
clinically-validated applications to improve the performance, capacity, and efficacy of …

Advancing precision medicine: a review of innovative in silico approaches for drug development, clinical pharmacology and personalized healthcare

L Marques, B Costa, M Pereira, A Silva, J Santos… - Pharmaceutics, 2024 - mdpi.com
The landscape of medical treatments is undergoing a transformative shift. Precision
medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and …

Trustworthy llms: a survey and guideline for evaluating large language models' alignment

Y Liu, Y Yao, JF Ton, X Zhang, R Guo, H Cheng… - arxiv preprint arxiv …, 2023 - arxiv.org
Ensuring alignment, which refers to making models behave in accordance with human
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …

Explainable AI-driven IoMT fusion: Unravelling techniques, opportunities, and challenges with Explainable AI in healthcare

NA Wani, R Kumar, J Bedi, I Rida - Information Fusion, 2024 - Elsevier
Abstract Background and Objective: Artificial Intelligence (AI) has shown significant
advancements across several industries, including healthcare, using better fusion …

Quantum computing for healthcare: A review

R Ur Rasool, HF Ahmad, W Rafique, A Qayyum… - Future Internet, 2023 - mdpi.com
In recent years, the interdisciplinary field of quantum computing has rapidly developed and
garnered substantial interest from both academia and industry due to its ability to process …

Towards Risk‐Free Trustworthy Artificial Intelligence: Significance and Requirements

L Alzubaidi, A Al-Sabaawi, J Bai… - … Journal of Intelligent …, 2023 - Wiley Online Library
Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …

An empirical study of pre-trained model reuse in the hugging face deep learning model registry

W Jiang, N Synovic, M Hyatt… - 2023 IEEE/ACM 45th …, 2023 - ieeexplore.ieee.org
Deep Neural Networks (DNNs) are being adopted as components in software systems.
Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the …

[HTML][HTML] Enhancing Internet of Medical Things security with artificial intelligence: A comprehensive review

S Messinis, N Temenos, NE Protonotarios… - Computers in biology …, 2024 - Elsevier
Over the past five years, interest in the literature regarding the security of the Internet of
Medical Things (IoMT) has increased. Due to the enhanced interconnectedness of IoMT …

Interpretable machine learning for discovery: Statistical challenges and opportunities

GI Allen, L Gan, L Zheng - Annual Review of Statistics and Its …, 2023 - annualreviews.org
New technologies have led to vast troves of large and complex data sets across many
scientific domains and industries. People routinely use machine learning techniques not …

Machine learning for multimodal mental health detection: a systematic review of passive sensing approaches

LS Khoo, MK Lim, CY Chong, R McNaney - Sensors, 2024 - mdpi.com
As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …