AI applications in HIV research: advances and future directions
With the increasing application of artificial intelligence (AI) in medical research, studies on the human immunodeficiency virus type 1(HIV-1) and acquired immunodeficiency syndrome (AIDS) have become more in-depth. Integrating AI with technologies like single-cell sequencing enables precise biomark...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-02-01
|
| Series: | Frontiers in Microbiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmicb.2025.1541942/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850025500113633280 |
|---|---|
| author | Ruyi Jin Ruyi Jin Ruyi Jin Ruyi Jin Li Zhang Li Zhang Li Zhang Li Zhang |
| author_facet | Ruyi Jin Ruyi Jin Ruyi Jin Ruyi Jin Li Zhang Li Zhang Li Zhang Li Zhang |
| author_sort | Ruyi Jin |
| collection | DOAJ |
| description | With the increasing application of artificial intelligence (AI) in medical research, studies on the human immunodeficiency virus type 1(HIV-1) and acquired immunodeficiency syndrome (AIDS) have become more in-depth. Integrating AI with technologies like single-cell sequencing enables precise biomarker identification and improved therapeutic targeting. This review aims to explore the advancements in AI technologies and their applications across various facets of HIV research, including viral mechanisms, diagnostic innovations, therapeutic strategies, and prevention efforts. Despite challenges like data limitations and model interpretability, AI holds significant potential in advancing HIV-1 management and contributing to global health goals. |
| format | Article |
| id | doaj-art-32df41f3dc8c4ec6808aab72b34e6558 |
| institution | DOAJ |
| issn | 1664-302X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Microbiology |
| spelling | doaj-art-32df41f3dc8c4ec6808aab72b34e65582025-08-20T03:00:50ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2025-02-011610.3389/fmicb.2025.15419421541942AI applications in HIV research: advances and future directionsRuyi Jin0Ruyi Jin1Ruyi Jin2Ruyi Jin3Li Zhang4Li Zhang5Li Zhang6Li Zhang7Department of Dermatology, The First Hospital of China Medical University, Shenyang, ChinaNHC Key Laboratory of Immunodermatology, China Medical University, Shenyang, ChinaKey Laboratory of Immunodermatology, China Medical University, Ministry of Education, Shenyang, ChinaNational and Local Joint Engineering Research Center of Immunodermatological Theranostics, Shenyang, ChinaDepartment of Dermatology, The First Hospital of China Medical University, Shenyang, ChinaNHC Key Laboratory of Immunodermatology, China Medical University, Shenyang, ChinaKey Laboratory of Immunodermatology, China Medical University, Ministry of Education, Shenyang, ChinaNational and Local Joint Engineering Research Center of Immunodermatological Theranostics, Shenyang, ChinaWith the increasing application of artificial intelligence (AI) in medical research, studies on the human immunodeficiency virus type 1(HIV-1) and acquired immunodeficiency syndrome (AIDS) have become more in-depth. Integrating AI with technologies like single-cell sequencing enables precise biomarker identification and improved therapeutic targeting. This review aims to explore the advancements in AI technologies and their applications across various facets of HIV research, including viral mechanisms, diagnostic innovations, therapeutic strategies, and prevention efforts. Despite challenges like data limitations and model interpretability, AI holds significant potential in advancing HIV-1 management and contributing to global health goals.https://www.frontiersin.org/articles/10.3389/fmicb.2025.1541942/fullHIV-human immunodeficiency virusacquired immuno deficiency syndrome (AIDS)artificial intelligence - AImachine learningvirologydeep learning |
| spellingShingle | Ruyi Jin Ruyi Jin Ruyi Jin Ruyi Jin Li Zhang Li Zhang Li Zhang Li Zhang AI applications in HIV research: advances and future directions Frontiers in Microbiology HIV-human immunodeficiency virus acquired immuno deficiency syndrome (AIDS) artificial intelligence - AI machine learning virology deep learning |
| title | AI applications in HIV research: advances and future directions |
| title_full | AI applications in HIV research: advances and future directions |
| title_fullStr | AI applications in HIV research: advances and future directions |
| title_full_unstemmed | AI applications in HIV research: advances and future directions |
| title_short | AI applications in HIV research: advances and future directions |
| title_sort | ai applications in hiv research advances and future directions |
| topic | HIV-human immunodeficiency virus acquired immuno deficiency syndrome (AIDS) artificial intelligence - AI machine learning virology deep learning |
| url | https://www.frontiersin.org/articles/10.3389/fmicb.2025.1541942/full |
| work_keys_str_mv | AT ruyijin aiapplicationsinhivresearchadvancesandfuturedirections AT ruyijin aiapplicationsinhivresearchadvancesandfuturedirections AT ruyijin aiapplicationsinhivresearchadvancesandfuturedirections AT ruyijin aiapplicationsinhivresearchadvancesandfuturedirections AT lizhang aiapplicationsinhivresearchadvancesandfuturedirections AT lizhang aiapplicationsinhivresearchadvancesandfuturedirections AT lizhang aiapplicationsinhivresearchadvancesandfuturedirections AT lizhang aiapplicationsinhivresearchadvancesandfuturedirections |