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Deep Learning Applications in Surgery: Current Uses and Future Directions.
Morris, Miranda X; Rajesh, Aashish; Asaad, Malke; Hassan, Abbas; Saadoun, Rakan; Butler, Charles E.
Afiliação
  • Morris MX; 12277Duke University School of Medicine, Durham, NC, USA.
  • Rajesh A; 101571Duke Pratt School of Engineering, Durham, NC, USA.
  • Asaad M; Department of Surgery, 14742University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
  • Hassan A; Department of Plastic Surgery, 6595University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
  • Saadoun R; Department of Plastic Surgery, 571198The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Butler CE; Department of Plastic Surgery, 6595University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Am Surg ; 89(1): 36-42, 2023 Jan.
Article em En | MEDLINE | ID: mdl-35567312
Deep learning (DL) is a subset of machine learning that is rapidly gaining traction in surgical fields. Its tremendous capacity for powerful data-driven problem-solving has generated computational breakthroughs in many realms, with the fields of medicine and surgery becoming increasingly prominent avenues. Through its multi-layer architecture of interconnected neural networks, DL enables feature extraction and pattern recognition of highly complex and large-volume data. Across various surgical specialties, DL is being applied to optimize both preoperative planning and intraoperative performance in new and innovative ways. Surgeons are now able to integrate deep learning tools into their practice to improve patient safety and outcomes. Through this review, we explore the applications of deep learning in surgery and related subspecialties with an aim to shed light on the practical utilization of this technology in the present and near future.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / Medicina Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / Medicina Idioma: En Ano de publicação: 2023 Tipo de documento: Article