{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["2023"],"submitter":["Ampofo JW"],"pubmed_abstract":["<h4>Introduction</h4>Recent advancements in technology have propelled the applications of artificial intelligence (AI) in various sectors, including healthcare. Medical imaging has benefited from AI by reducing radiation risks through algorithms used in examinations, referral protocols, and scan justification. This research work assessed the level of knowledge and awareness of 225 second- to fourth-year medical imaging students from public universities in Ghana about AI and its prospects in medical imaging.<h4>Methods</h4>This was a cross-sectional quantitative study design that used a closed-ended questionnaire with dichotomous questions, designed on Google Forms, and distributed to students through their various class WhatsApp platforms. Responses were entered into an Excel spreadsheet a"],"journal":["Radiology research and practice"],"pagination":["4704342"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10287516"],"repository":["biostudies-literature"],"pubmed_title":["Assessing the Level of Understanding (Knowledge) and Awareness of Diagnostic Imaging Students in Ghana on Artificial Intelligence and Its Applications in Medical Imaging."],"pmcid":["PMC10287516"],"pubmed_authors":["Emery CV","Ampofo JW","Ofori IN"],"additional_accession":[]},"is_claimable":false,"name":"Assessing the Level of Understanding (Knowledge) and Awareness of Diagnostic Imaging Students in Ghana on Artificial Intelligence and Its Applications in Medical Imaging.","description":"<h4>Introduction</h4>Recent advancements in technology have propelled the applications of artificial intelligence (AI) in various sectors, including healthcare. Medical imaging has benefited from AI by reducing radiation risks through algorithms used in examinations, referral protocols, and scan justification. This research work assessed the level of knowledge and awareness of 225 second- to fourth-year medical imaging students from public universities in Ghana about AI and its prospects in medical imaging.<h4>Methods</h4>This was a cross-sectional quantitative study design that used a closed-ended questionnaire with dichotomous questions, designed on Google Forms, and distributed to students through their various class WhatsApp platforms. Responses were entered into an Excel spreadsheet a","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023","modification":"2025-04-22T09:44:36.836Z","creation":"2025-04-22T09:44:36.836Z"},"accession":"S-EPMC10287516","cross_references":{"pubmed":["37362195"],"doi":["10.1155/2023/4704342"]}}