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Computer-Assisted Clinical Diagnosis and Treatment.
Hamid, Nadia; Portnoy, Jay M; Pandya, Aarti.
Afiliação
  • Hamid N; Department of Internal Medicine, University of Kansas Hospital, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA.
  • Portnoy JM; Division of Allergy, Immunology, Pulmonary and Sleep Medicine, Children's Mercy Hospital and University of Missouri-Kansas City, 2401 Gillham Road, Kansas City, MO, 64108, USA.
  • Pandya A; Division of Allergy, Immunology, Pulmonary and Sleep Medicine, Children's Mercy Hospital and University of Missouri-Kansas City, 2401 Gillham Road, Kansas City, MO, 64108, USA. appandya@cmh.edu.
Curr Allergy Asthma Rep ; 23(9): 509-517, 2023 09.
Article em En | MEDLINE | ID: mdl-37351722
PURPOSE OF REVIEW: Computer-assisted diagnosis and treatment (CAD/CAT) is a rapidly growing field of medicine that uses computer technology and telehealth to aid in the diagnosis and treatment of various diseases. The purpose of this paper is to provide a review on computer-assisted diagnosis and treatment. This technology gives providers access to diagnostic tools and treatment options so that they can make more informed decisions leading to improved patient outcomes. RECENT FINDINGS: CAD/CAT has expanded in allergy and immunology in the form of digital tools that enable remote patient monitoring such as digital inhalers, pulmonary function tests, and E-diaries. By incorporating this information into electronic medical records (EMRs), providers can use this information to make the best, evidence-based diagnosis and to recommend treatment that is likely to be most effective. A major benefit of CAD/CAT is that by analyzing large amounts of data, tailored recommendations can be made to improve patient outcomes and reduce the risk of adverse events. Machine learning can assist with medical data acquisition, feature extraction, interpretation, and decision support. It is important to note that this technology is not meant to replace human professionals. Instead, it is designed to assist healthcare professionals to better diagnose and treat patients.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diagnóstico por Computador / Telemedicina Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diagnóstico por Computador / Telemedicina Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos