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[HTML][HTML] Privacy-preserving artificial intelligence in healthcare: Techniques and applications
There has been an increasing interest in translating artificial intelligence (AI) research into
clinically-validated applications to improve the performance, capacity, and efficacy of …
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 …
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
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) …
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
Abstract Background and Objective: Artificial Intelligence (AI) has shown significant
advancements across several industries, including healthcare, using better fusion …
advancements across several industries, including healthcare, using better fusion …
Quantum computing for healthcare: A review
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 …
garnered substantial interest from both academia and industry due to its ability to process …
Towards Risk‐Free Trustworthy Artificial Intelligence: Significance and Requirements
Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
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
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 …
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
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 …
Medical Things (IoMT) has increased. Due to the enhanced interconnectedness of IoMT …
Interpretable machine learning for discovery: Statistical challenges and opportunities
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 …
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
As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …