Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/7720
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dc.contributor.authorSiddiqui, Mohd Faizanen_US
dc.contributor.authorMouna, Azaroualen_US
dc.contributor.authorVillela, Ricardoen_US
dc.contributor.authorKalmatov, Romanen_US
dc.contributor.authorBoueri, Myriamen_US
dc.contributor.authorBay, Sadiken_US
dc.contributor.authorBabu, P. Sureshen_US
dc.contributor.authorEtry, Hadyen_US
dc.contributor.authorMitalipova, Ainuraen_US
dc.contributor.authorBaig, Mirza Mohammed Ismailen_US
dc.contributor.authorSaad, Elio Assaaden_US
dc.contributor.authorMilan, Milanieen_US
dc.contributor.authorBazieva, Aliiaen_US
dc.contributor.authorKurbanaliev, Abdikerimen_US
dc.date.accessioned2025-01-10T07:39:48Z-
dc.date.available2025-01-10T07:39:48Z-
dc.date.issued2024-01-01-
dc.identifier.isbn[9780443275746, 9780443275753]-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/7720-
dc.description.abstractThe field of genomics is progressing via a scientific framework that significantly depends on the analysis and interpretation of large datasets. The development of advanced data creation methods in genomics has resulted in a flood of genetic data. Abundant knowledge of genetic data has enabled artificial intelligence, especially deep learning approaches, to be extremely beneficial in revealing significant discoveries and patterns. On the other hand, in low-income and middle-income countries (LMICs), the lack of clinical genetic resources and restricted access to genetic screening programs increases children's and families' risk of delayed diagnosis. This chapter emphasizes development and utilization of deep learning methodologies in various facets of human genomics to address global health challenges. This necessitates the implementation of screening and risk assessment measures at the point of care, tailored to the specific local, economic, and sociocultural circumstances of LMIC's populations.en_US
dc.language.isoengen_US
dc.subjectDeep learningen_US
dc.subjectGenetic syndromesen_US
dc.subjectGenomicsen_US
dc.subjectGlobal healthen_US
dc.subjectLow- and middle-income countries (LMICs)en_US
dc.titleInequality in genetic healthcare: Bridging gaps with deep learning innovations in low-income and middle-income countriesen_US
dc.typeBook Chapteren_US
dc.identifier.doi10.1016/B978-0-443-27574-6.00003-5-
dc.identifier.scopus2-s2.0-85213195795-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85213195795-
dc.contributor.affiliationFaculty of Medicineen_US
dc.description.startpage397en_US
dc.description.endpage410en_US
dc.date.catalogued2025-01-10-
dc.description.statusPublisheden_US
dc.relation.ispartoftextDeep Learning in Genetics and Genomics, Vo. 1en_US
Appears in Collections:Faculty of Medicine
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