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The role of machine learning in clinical research: transforming the future of evidence generation
Background Interest in the application of machine learning (ML) to the design, conduct, and
analysis of clinical trials has grown, but the evidence base for such applications has not …
analysis of clinical trials has grown, but the evidence base for such applications has not …
High-performance medicine: the convergence of human and artificial intelligence
EJ Topol - Nature medicine, 2019 - nature.com
The use of artificial intelligence, and the deep-learning subtype in particular, has been
enabled by the use of labeled big data, along with markedly enhanced computing power …
enabled by the use of labeled big data, along with markedly enhanced computing power …
Gain: Missing data imputation using generative adversarial nets
We propose a novel method for imputing missing data by adapting the well-known
Generative Adversarial Nets (GAN) framework. Accordingly, we call our method Generative …
Generative Adversarial Nets (GAN) framework. Accordingly, we call our method Generative …
Explainable artificial intelligence models using real-world electronic health record data: a systematic sco** review
Objective To conduct a systematic sco** review of explainable artificial intelligence (XAI)
models that use real-world electronic health record data, categorize these techniques …
models that use real-world electronic health record data, categorize these techniques …
Donor heart selection: evidence-based guidelines for providers
The proposed donor heart selection guidelines provide evidence-based and expert-
consensus recommendations for the selection of donor hearts following brain death. These …
consensus recommendations for the selection of donor hearts following brain death. These …
The promise of machine learning applications in solid organ transplantation
Solid-organ transplantation is a life-saving treatment for end-stage organ disease in highly
selected patients. Alongside the tremendous progress in the last several decades, new …
selected patients. Alongside the tremendous progress in the last several decades, new …
INVASE: Instance-wise variable selection using neural networks
The advent of big data brings with it data with more and more dimensions and thus a
growing need to be able to efficiently select which features to use for a variety of problems …
growing need to be able to efficiently select which features to use for a variety of problems …
[HTML][HTML] Enhancing kidney transplant care through the integration of chatbot
Kidney transplantation is a critical treatment option for end-stage kidney disease patients,
offering improved quality of life and increased survival rates. However, the complexities of …
offering improved quality of life and increased survival rates. However, the complexities of …
Artificial intelligence in clinical decision support: a focused literature survey
Objectives: This survey analyses the latest literature contributions to clinical decision support
systems (DSSs) on a two-year period (2017-2018), focusing on the approaches that adopt …
systems (DSSs) on a two-year period (2017-2018), focusing on the approaches that adopt …
The future of Cardiothoracic surgery in Artificial intelligence
H Mumtaz, M Saqib, F Ansar, D Zargar… - Annals of Medicine …, 2022 - journals.lww.com
Humans' great and quick technological breakthroughs in the previous decade have
undoubtedly influenced how surgical procedures are executed in the operating room. AI is …
undoubtedly influenced how surgical procedures are executed in the operating room. AI is …