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Article
Statistics & Probability
Rina Foygel Barber et al.
ANNALS OF STATISTICS
(2023)
Article
Computer Science, Artificial Intelligence
Robin Mitra et al.
Summary: Gathering big datasets is crucial for machine learning in scientific areas, but missing data values pose challenges, especially when dealing with structured missingness. While tools exist to handle 'missing at random' data, structured missingness, where missing values show association or structure, presents new obstacles. This issue becomes increasingly important as machine learning studies aim to learn from larger volumes of heterogeneous data.
NATURE MACHINE INTELLIGENCE
(2023)
Review
Infectious Diseases
Bradley J. Langford et al.
Summary: The study estimated that approximately three-quarters of patients with COVID-19 receive antibiotic treatment, which is significantly higher than the estimated prevalence of bacterial co-infection. This suggests a potential for high rates of unnecessary antibiotic use in patients with COVID-19.
CLINICAL MICROBIOLOGY AND INFECTION
(2021)
Article
Ethics
Blake Murdoch
Summary: The development of healthcare artificial intelligence is raising concerns about the protection of patient data in the hands of private entities. Additionally, the use of AI-driven methods also poses risks of privacy breaches. There is a need for appropriate regulations and safeguards to ensure data privacy and patient agency are maintained.
BMC MEDICAL ETHICS
(2021)
Letter
Medicine, General & Internal
Samuel G. Finlayson et al.
NEW ENGLAND JOURNAL OF MEDICINE
(2021)
Review
Medicine, General & Internal
Constanza L. Andaur Navarro et al.
Summary: A systematic review was conducted to assess the methodological quality of prediction models developed using machine learning techniques in various medical specialties between January 1, 2018 and December 31, 2019. The review found that most studies exhibited poor methodological quality and high risk of bias, with factors such as small study size, inadequate handling of missing data, and improper overfitting assessment contributing to this bias. Efforts to improve the design, conduct, reporting, and validation of these studies are necessary to enhance the application of machine learning based prediction models in clinical practice.
BMJ-BRITISH MEDICAL JOURNAL
(2021)
Article
Health Care Sciences & Services
Susanne Gaube et al.
Summary: This study found that radiologists rated diagnostic advice as lower quality when it appeared to come from an AI system, while less experienced physicians did not have this bias. Diagnostic accuracy significantly decreased when participants received inaccurate advice, regardless of the purported source being AI or human experts. Therefore, important considerations need to be made when deploying advice in clinical environments, whether it is coming from AI or non-AI sources.
NPJ DIGITAL MEDICINE
(2021)
Editorial Material
Infectious Diseases
Lesley Heesom et al.
JOURNAL OF GLOBAL ANTIMICROBIAL RESISTANCE
(2020)
Article
Medicine, General & Internal
Christopher J. Kelly et al.
Review
Oncology
Sarah E. Jackson et al.
INTERNATIONAL JOURNAL OF CANCER
(2015)
Review
Cardiac & Cardiovascular Systems
Linda L. Coventry et al.
Article
Engineering, Civil
Armen Der Kiureghian et al.