Where medical statistics meets artificial intelligence

DJ Hunter, C Holmes - New England Journal of Medicine, 2023 - Mass Medical Soc
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Application of artificial intelligence techniques for monkeypox: a systematic review

K Chadaga, S Prabhu, N Sampathila, S Nireshwalya… - Diagnostics, 2023 - mdpi.com
Monkeypox or Mpox is an infectious virus predominantly found in Africa. It has spread to
many countries since its latest outbreak. Symptoms such as headaches, chills, and fever are …

The integration of clinical trials with the practice of medicine: repairing a house divided

DC Angus, AJ Huang, RJ Lewis, AP Abernethy… - Jama, 2024 - jamanetwork.com
Importance Optimal health care delivery, both now and in the future, requires a continuous
loop of knowledge generation, dissemination, and uptake on how best to provide care, not …

Artificial intelligence and open science in discovery of disease-modifying medicines for Alzheimer's disease

F Cheng, F Wang, J Tang, Y Zhou, Z Fu, P Zhang… - Cell Reports …, 2024 - cell.com
The high failure rate of clinical trials in Alzheimer's disease (AD) and AD-related dementia
(ADRD) is due to a lack of understanding of the pathophysiology of disease, and this deficit …

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 …

[HTML][HTML] The impact of digital hospitals on patient and clinician experience: Systematic review and qualitative evidence synthesis

OJ Canfell, L Woods, Y Meshkat, J Krivit… - Journal of Medical …, 2024 - jmir.org
Background The digital transformation of health care is advancing rapidly. A well-accepted
framework for health care improvement is the Quadruple Aim: improved clinician …

Diffusion models for causal discovery via topological ordering

P Sanchez, X Liu, AQ O'Neil, SA Tsaftaris - arxiv preprint arxiv …, 2022 - arxiv.org
Discovering causal relations from observational data becomes possible with additional
assumptions such as considering the functional relations to be constrained as nonlinear with …

Learning across diverse biomedical data modalities and cohorts: Challenges and opportunities for innovation

S Rajendran, W Pan, MR Sabuncu, Y Chen, J Zhou… - Patterns, 2024 - cell.com
In healthcare, machine learning (ML) shows significant potential to augment patient care,
improve population health, and streamline healthcare workflows. Realizing its full potential …

Counterfactual learning on graphs: A survey

Z Guo, Z Wu, T **ao, C Aggarwal, H Liu… - Machine Intelligence …, 2025 - Springer
Graph-structured data are pervasive in the real-world such as social networks, molecular
graphs and transaction networks. Graph neural networks (GNNs) have achieved great …

Applications of machine learning on electronic health record data to combat antibiotic resistance

SE Blechman, ES Wright - The Journal of Infectious Diseases, 2024 - academic.oup.com
There is growing excitement about the clinical use of artificial intelligence and machine
learning (ML) technologies. Advancements in computing and the accessibility of ML …