Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387356991> ?p ?o ?g. }
- W4387356991 abstract "Abstract Artificial intelligence tools, particularly convolutional neural networks (CNNs), are transforming healthcare by enhancing predictive, diagnostic, and decision-making capabilities. This review provides an accessible and practical explanation of CNNs for clinicians and highlights their relevance in medical image analysis. CNNs have shown themselves to be exceptionally useful in computer vision, a field that enables machines to ‘see’ and interpret visual data. Understanding how these models work can help clinicians leverage their full potential, especially as artificial intelligence continues to evolve and integrate into healthcare. CNNs have already demonstrated their efficacy in diverse medical fields, including radiology, histopathology, and medical photography. In radiology, CNNs have been used to automate the assessment of conditions such as pneumonia, pulmonary embolism, and rectal cancer. In histopathology, CNNs have been used to assess and classify colorectal polyps, gastric epithelial tumours, as well as assist in the assessment of multiple malignancies. In medical photography, CNNs have been used to assess retinal diseases and skin conditions, and to detect gastric and colorectal polyps during endoscopic procedures. In surgical laparoscopy, they may provide intraoperative assistance to surgeons, helping interpret surgical anatomy and demonstrate safe dissection zones. The integration of CNNs into medical image analysis promises to enhance diagnostic accuracy, streamline workflow efficiency, and expand access to expert-level image analysis, contributing to the ultimate goal of delivering further improvements in patient and healthcare outcomes." @default.
- W4387356991 created "2023-10-06" @default.
- W4387356991 creator A5034251166 @default.
- W4387356991 creator A5046076979 @default.
- W4387356991 creator A5064834972 @default.
- W4387356991 creator A5071976079 @default.
- W4387356991 creator A5083781406 @default.
- W4387356991 creator A5087008817 @default.
- W4387356991 date "2023-10-04" @default.
- W4387356991 modified "2023-10-06" @default.
- W4387356991 title "Computer image analysis with artificial intelligence: a practical introduction to convolutional neural networks for medical professionals" @default.
- W4387356991 cites W2033991895 @default.
- W4387356991 cites W2142356139 @default.
- W4387356991 cites W2291961022 @default.
- W4387356991 cites W2581082771 @default.
- W4387356991 cites W2608231518 @default.
- W4387356991 cites W2789532252 @default.
- W4387356991 cites W2809254203 @default.
- W4387356991 cites W2899525417 @default.
- W4387356991 cites W2906295032 @default.
- W4387356991 cites W2908052439 @default.
- W4387356991 cites W2993820249 @default.
- W4387356991 cites W2998401461 @default.
- W4387356991 cites W3004016611 @default.
- W4387356991 cites W3008205232 @default.
- W4387356991 cites W3019938913 @default.
- W4387356991 cites W3022403657 @default.
- W4387356991 cites W3033492597 @default.
- W4387356991 cites W3034225237 @default.
- W4387356991 cites W3036881855 @default.
- W4387356991 cites W3048881824 @default.
- W4387356991 cites W3080906242 @default.
- W4387356991 cites W3098150009 @default.
- W4387356991 cites W3100777112 @default.
- W4387356991 cites W3101230421 @default.
- W4387356991 cites W3101294892 @default.
- W4387356991 cites W3141047505 @default.
- W4387356991 cites W3148150040 @default.
- W4387356991 cites W3156331990 @default.
- W4387356991 cites W3157319724 @default.
- W4387356991 cites W3162300195 @default.
- W4387356991 cites W3217222169 @default.
- W4387356991 cites W4200563352 @default.
- W4387356991 cites W4221072997 @default.
- W4387356991 cites W4225919190 @default.
- W4387356991 cites W4283792648 @default.
- W4387356991 cites W4283806161 @default.
- W4387356991 cites W4285679076 @default.
- W4387356991 cites W4296156606 @default.
- W4387356991 cites W4297902779 @default.
- W4387356991 cites W4307511335 @default.
- W4387356991 doi "https://doi.org/10.1093/postmj/qgad095" @default.
- W4387356991 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37794609" @default.
- W4387356991 hasPublicationYear "2023" @default.
- W4387356991 type Work @default.
- W4387356991 citedByCount "0" @default.
- W4387356991 crossrefType "journal-article" @default.
- W4387356991 hasAuthorship W4387356991A5034251166 @default.
- W4387356991 hasAuthorship W4387356991A5046076979 @default.
- W4387356991 hasAuthorship W4387356991A5064834972 @default.
- W4387356991 hasAuthorship W4387356991A5071976079 @default.
- W4387356991 hasAuthorship W4387356991A5083781406 @default.
- W4387356991 hasAuthorship W4387356991A5087008817 @default.
- W4387356991 hasConcept C119857082 @default.
- W4387356991 hasConcept C126838900 @default.
- W4387356991 hasConcept C142724271 @default.
- W4387356991 hasConcept C154945302 @default.
- W4387356991 hasConcept C177212765 @default.
- W4387356991 hasConcept C19527891 @default.
- W4387356991 hasConcept C31601959 @default.
- W4387356991 hasConcept C41008148 @default.
- W4387356991 hasConcept C71924100 @default.
- W4387356991 hasConcept C77088390 @default.
- W4387356991 hasConcept C81363708 @default.
- W4387356991 hasConceptScore W4387356991C119857082 @default.
- W4387356991 hasConceptScore W4387356991C126838900 @default.
- W4387356991 hasConceptScore W4387356991C142724271 @default.
- W4387356991 hasConceptScore W4387356991C154945302 @default.
- W4387356991 hasConceptScore W4387356991C177212765 @default.
- W4387356991 hasConceptScore W4387356991C19527891 @default.
- W4387356991 hasConceptScore W4387356991C31601959 @default.
- W4387356991 hasConceptScore W4387356991C41008148 @default.
- W4387356991 hasConceptScore W4387356991C71924100 @default.
- W4387356991 hasConceptScore W4387356991C77088390 @default.
- W4387356991 hasConceptScore W4387356991C81363708 @default.
- W4387356991 hasFunder F4320332161 @default.
- W4387356991 hasLocation W43873569911 @default.
- W4387356991 hasLocation W43873569912 @default.
- W4387356991 hasOpenAccess W4387356991 @default.
- W4387356991 hasPrimaryLocation W43873569911 @default.
- W4387356991 hasRelatedWork W1995688399 @default.
- W4387356991 hasRelatedWork W2034850138 @default.
- W4387356991 hasRelatedWork W2050807133 @default.
- W4387356991 hasRelatedWork W2055993415 @default.
- W4387356991 hasRelatedWork W2158402533 @default.
- W4387356991 hasRelatedWork W2443196326 @default.
- W4387356991 hasRelatedWork W3086104399 @default.
- W4387356991 hasRelatedWork W328486336 @default.
- W4387356991 hasRelatedWork W4323287533 @default.
- W4387356991 hasRelatedWork W4360994352 @default.