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...
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...
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...
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...
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...
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...
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...
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...
Machine learning models may be integrated into clinical decision support (CDS) systems to identify children at risk of specific diagnoses or clinical deterioration to provide evidence-based recommendations. This use of artificial intelligence models ...
BACKGROUND: Methods that can automate, support, and streamline the preanesthesia evaluation process may improve resource utilization and efficiency. Natural language processing (NLP) involves the extraction of relevant information from unstructured t...
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