Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385154982> ?p ?o ?g. }
Showing items 1 to 99 of
99
with 100 items per page.
- W4385154982 abstract "Abstract Introduction Aneurysmal subarachnoid hemorrhage (SAH) is a subtype of hemorrhagic stroke with thirty-day mortality as high as 40%. Given the expansion of Machine Learning (ML) and Artificial intelligence (AI) methods in health care, SAH patients desperately need an integrated AI system that detects, segments, and supports clinical decisions based on presentation and severity. Objectives This review aims to synthesize the current state of the art of AI and ML tools for the management of SAH patients alongside providing an up-to-date account of future horizons in patient care. Methods We performed a systematic review through various databases such as Cochrane Central Register of Controlled Trials, MEDLINE, Scopus, Cochrane Database of Systematic Reviews, and Embase. Results A total of 507 articles were identified. Following extensive revision, only 21 articles were relevant. Two studies reported improved mortality prediction using Glasgow Coma Scale and biomarkers such as Neutrophil to Lymphocyte Ratio and glucose. One study reported that ffANN is equal to the SAHIT and VASOGRADE scores. One study reported that metabolic biomarkers Ornithine, Symmetric Dimethylarginine, and Dimethylguanidine Valeric acid were associated with poor outcomes. Nine studies reported improved prediction of complications and reduction in latency until intervention using clinical scores and imaging. Four studies reported accurate prediction of aneurysmal rupture based on size, shape, and CNN. One study reported AI-assisted Robotic Transcranial Doppler as a substitute for clinicians. Conclusion AI/ML technologies possess tremendous potential in accelerating SAH systems-of- care. Keeping abreast of developments is vital in advancing timely interventions for critical diseases." @default.
- W4385154982 created "2023-07-23" @default.
- W4385154982 creator A5019565749 @default.
- W4385154982 creator A5033370951 @default.
- W4385154982 creator A5033432372 @default.
- W4385154982 creator A5036500415 @default.
- W4385154982 creator A5038851501 @default.
- W4385154982 creator A5043107361 @default.
- W4385154982 creator A5043194639 @default.
- W4385154982 creator A5085592232 @default.
- W4385154982 date "2023-07-23" @default.
- W4385154982 modified "2023-10-12" @default.
- W4385154982 title "Artificial Intelligence and Machine Learning in Aneurysmal Subarachnoid Hemorrhage: Future Promises, Perils, and Practicalities" @default.
- W4385154982 cites W2131338198 @default.
- W4385154982 cites W2899722123 @default.
- W4385154982 cites W2937404770 @default.
- W4385154982 cites W2946535957 @default.
- W4385154982 cites W2955800301 @default.
- W4385154982 cites W2956418867 @default.
- W4385154982 cites W3012280898 @default.
- W4385154982 cites W3036327316 @default.
- W4385154982 cites W3103346582 @default.
- W4385154982 cites W3123816888 @default.
- W4385154982 cites W3128761879 @default.
- W4385154982 cites W3134815439 @default.
- W4385154982 cites W3147817754 @default.
- W4385154982 cites W3201357619 @default.
- W4385154982 cites W4200025212 @default.
- W4385154982 cites W4210943902 @default.
- W4385154982 cites W4220857284 @default.
- W4385154982 cites W4224289711 @default.
- W4385154982 cites W4235117781 @default.
- W4385154982 cites W4282014333 @default.
- W4385154982 cites W4283022454 @default.
- W4385154982 cites W4308993668 @default.
- W4385154982 doi "https://doi.org/10.1101/2023.07.18.23292822" @default.
- W4385154982 hasPublicationYear "2023" @default.
- W4385154982 type Work @default.
- W4385154982 citedByCount "0" @default.
- W4385154982 crossrefType "posted-content" @default.
- W4385154982 hasAuthorship W4385154982A5019565749 @default.
- W4385154982 hasAuthorship W4385154982A5033370951 @default.
- W4385154982 hasAuthorship W4385154982A5033432372 @default.
- W4385154982 hasAuthorship W4385154982A5036500415 @default.
- W4385154982 hasAuthorship W4385154982A5038851501 @default.
- W4385154982 hasAuthorship W4385154982A5043107361 @default.
- W4385154982 hasAuthorship W4385154982A5043194639 @default.
- W4385154982 hasAuthorship W4385154982A5085592232 @default.
- W4385154982 hasBestOaLocation W43851549821 @default.
- W4385154982 hasConcept C118552586 @default.
- W4385154982 hasConcept C119857082 @default.
- W4385154982 hasConcept C126322002 @default.
- W4385154982 hasConcept C141071460 @default.
- W4385154982 hasConcept C154945302 @default.
- W4385154982 hasConcept C17624336 @default.
- W4385154982 hasConcept C17744445 @default.
- W4385154982 hasConcept C177713679 @default.
- W4385154982 hasConcept C189708586 @default.
- W4385154982 hasConcept C199539241 @default.
- W4385154982 hasConcept C27415008 @default.
- W4385154982 hasConcept C2776478404 @default.
- W4385154982 hasConcept C2777736543 @default.
- W4385154982 hasConcept C2779473830 @default.
- W4385154982 hasConcept C41008148 @default.
- W4385154982 hasConcept C71924100 @default.
- W4385154982 hasConcept C95190672 @default.
- W4385154982 hasConceptScore W4385154982C118552586 @default.
- W4385154982 hasConceptScore W4385154982C119857082 @default.
- W4385154982 hasConceptScore W4385154982C126322002 @default.
- W4385154982 hasConceptScore W4385154982C141071460 @default.
- W4385154982 hasConceptScore W4385154982C154945302 @default.
- W4385154982 hasConceptScore W4385154982C17624336 @default.
- W4385154982 hasConceptScore W4385154982C17744445 @default.
- W4385154982 hasConceptScore W4385154982C177713679 @default.
- W4385154982 hasConceptScore W4385154982C189708586 @default.
- W4385154982 hasConceptScore W4385154982C199539241 @default.
- W4385154982 hasConceptScore W4385154982C27415008 @default.
- W4385154982 hasConceptScore W4385154982C2776478404 @default.
- W4385154982 hasConceptScore W4385154982C2777736543 @default.
- W4385154982 hasConceptScore W4385154982C2779473830 @default.
- W4385154982 hasConceptScore W4385154982C41008148 @default.
- W4385154982 hasConceptScore W4385154982C71924100 @default.
- W4385154982 hasConceptScore W4385154982C95190672 @default.
- W4385154982 hasLocation W43851549821 @default.
- W4385154982 hasOpenAccess W4385154982 @default.
- W4385154982 hasPrimaryLocation W43851549821 @default.
- W4385154982 hasRelatedWork W1895224385 @default.
- W4385154982 hasRelatedWork W2001309417 @default.
- W4385154982 hasRelatedWork W2122489679 @default.
- W4385154982 hasRelatedWork W2132791223 @default.
- W4385154982 hasRelatedWork W2418011111 @default.
- W4385154982 hasRelatedWork W2909928837 @default.
- W4385154982 hasRelatedWork W2964601175 @default.
- W4385154982 hasRelatedWork W4307384190 @default.
- W4385154982 hasRelatedWork W4318979796 @default.
- W4385154982 hasRelatedWork W4380423232 @default.
- W4385154982 isParatext "false" @default.
- W4385154982 isRetracted "false" @default.
- W4385154982 workType "article" @default.