AIMC Topic: Decision Support Systems, Clinical
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An Artificial Intelligence Tool for Clinical Decision Support and Protocol Selection for Brain MRI.
AJNR. American journal of neuroradiology
Dec 15, 2022
BACKGROUND AND PURPOSE: Protocolling, the process of determining the most appropriate acquisition parameters for an imaging study, is time-consuming and produces variable results depending on the performing physician. The purpose of this study was to...
Electronic Health Record Optimization for Artificial Intelligence.
Clinics in laboratory medicine
Dec 14, 2022
Laboratory clinical decision support (CDS) typically relies on data from the electronic health record (EHR). The implementation of a sustainable, effective laboratory CDS program requires a commitment to standardization and harmonization of key EHR d...
Clinical Artificial Intelligence: Design Principles and Fallacies.
Clinics in laboratory medicine
Dec 13, 2022
Clinical artificial intelligence (AI)/machine learning (ML) is anticipated to offer new abilities in clinical decision support, diagnostic reasoning, precision medicine, clinical operational support, and clinical research, but careful concern is need...
Artificial intelligence to support early diagnosis of temporomandibular disorders: A preliminary case study.
Journal of oral rehabilitation
Nov 3, 2022
BACKGROUND: Temporomandibular disorders (TMDs) are disabling conditions with a negative impact on the quality of life. Their diagnosis is a complex and multi-factorial process that should be conducted by experienced professionals, and most TMDs remai...
Developing an AI-assisted clinical decision support system to enhance in-patient holistic health care.
PloS one
Oct 31, 2022
Holistic health care (HHC) is a synonym for complete patient care, and as such an efficient clinical decision support system (CDSS) for HHC is critical to support the judgement of physician's decision in response of patient's physical, emotional, soc...
Artificial intelligence in intensive care: moving towards clinical decision support systems.
Minerva anestesiologica
Oct 26, 2022
The high complexity of care in the Intensive Care Unit environment has led, in the last decades, to a big effort in term of the improvement of patient's monitoring devices, increase of diagnostic and therapeutic opportunities, and development of elec...
Pivotal challenges in artificial intelligence and machine learning applications for neonatal care.
Seminars in fetal & neonatal medicine
Oct 13, 2022
Clinical decision support systems (CDSS) that are developed based on artificial intelligence and machine learning (AI/ML) approaches carry transformative potentials in improving the way neonatal care is practiced. From the use of the data available f...
Automated clinical decision support system with deep learning dose prediction and NTCP models to evaluate treatment complications in patients with esophageal cancer.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Sep 24, 2022
BACKGROUND AND PURPOSE: This study aims to investigate how accurate our deep learning (DL) dose prediction models for intensity modulated radiotherapy (IMRT) and pencil beam scanning (PBS) treatments, when chained with normal tissue complication prob...
The Challenges of Regulating Artificial Intelligence in Healthcare Comment on "Clinical Decision Support and New Regulatory Frameworks for Medical Devices: Are We Ready for It? - A Viewpoint Paper".
International journal of health policy and management
Sep 19, 2022
Regulation of health technologies must be rigorous, instilling trust among both healthcare providers and patients. This is especially important for the control and supervision of the growing use of artificial intelligence in healthcare. In this comme...
A clinical decision support system optimising adjuvant chemotherapy for colorectal cancers by integrating deep learning and pathological staging markers: a development and validation study.
The Lancet. Oncology
Aug 11, 2022
BACKGROUND: The DoMore-v1-CRC marker was recently developed using deep learning and conventional haematoxylin and eosin-stained tissue sections, and was observed to outperform established molecular and morphological markers of patient outcome after p...
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