dc.contributor.author | Kabir, Md Saif | |
dc.contributor.author | Alam, Shahed | |
dc.date.accessioned | 2024-10-28T05:00:15Z | |
dc.date.available | 2024-10-28T05:00:15Z | |
dc.date.copyright | ©2024 | |
dc.date.issued | 2024-07-03 | |
dc.identifier.citation | Kabir, M. S., & Alam, S. (2024). Impact of machine learning and deep learning on biomedical applications and healthcare industry. REFLECTION, 1, 142–149. | |
dc.identifier.isbn | 9789849906995 | |
dc.identifier.uri | http://hdl.handle.net/10361/24426 | |
dc.description | Cataloged from PDF version of the article. | en_US |
dc.description | Includes bibliographical references (pages 147-149). | |
dc.description.abstract | A new era of innovation and change in healthcare and medical
diagnostics has started as a result of the advancements in Machine
Learning (ML) and Deep Learning (DL). Machine learning and deep
learning are not just supplemental tools. They are also the catalysts for
a paradigm shift in healthcare industry that promises more efficient and
individualized healthcare solutions in the nearby future. The substantial
impacts of these cutting-edge algorithms on the biomedical applications
have been explored in this research paper. With the help of Artificial
Intelligence (AI) and its related field, researchers and healthcare
professionals now have access to technologies that can analyze large
and complicated datasets, extract insightful knowledge, diagnose
medical conditions and make incredibly precise predictions. | en_US |
dc.description.statementofresponsibility | Md Saif Kabir | |
dc.description.statementofresponsibility | Shahed Alam | |
dc.format.extent | 8 pages | |
dc.language.iso | en | en_US |
dc.publisher | BRAC University Research For Development Club (BURED) | en_US |
dc.rights | The BRAC University Research For Development Club (BURED) retains all rights. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
dc.subject | Biomedical engineering | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Deep learning | en_US |
dc.subject | Healthcare | en_US |
dc.subject | Data-driven insights | en_US |
dc.subject | Medical diagnostics | en_US |
dc.subject | Artificial intelligence | en_US |
dc.subject.lcsh | Artificial intelligence. | |
dc.subject.lcsh | Data mining. | |
dc.subject.lcsh | Healthcare. | |
dc.subject.lcsh | Medical care. | |
dc.subject.lcsh | Biomedical engineering. | |
dc.subject.lcsh | Machine learning. | |
dc.title | Impact of machine learning and deep learning on biomedical applications and healthcare industry | en_US |
dc.type | Article | en_US |