Artificial Intelligence in Translational Medicine
The huge advancement in Internet web facilities as well as the progress in computing and algorithm development, along with current innovations regarding high-throughput techniques, enable the scientific community to gain access to biological datasets, clinical data and several databases containing b...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | International Journal of Translational Medicine |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-8937/1/3/16 |
| _version_ | 1827672060002828288 |
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| author | Simone Brogi Vincenzo Calderone |
| author_facet | Simone Brogi Vincenzo Calderone |
| author_sort | Simone Brogi |
| collection | DOAJ |
| description | The huge advancement in Internet web facilities as well as the progress in computing and algorithm development, along with current innovations regarding high-throughput techniques, enable the scientific community to gain access to biological datasets, clinical data and several databases containing billions of pieces of information concerning scientific knowledge. Consequently, during the last decade the system for managing, analyzing, processing and extrapolating information from scientific data has been considerably modified in several fields, including the medical one. As a consequence of the mentioned scenario, scientific vocabulary was enriched by novel lexicons such as machine learning (ML)/deep learning (DL) and overall artificial intelligence (AI). Beyond the terminology, these computational techniques are revolutionizing the scientific research in drug discovery pitch, from the preclinical studies to clinical investigation. Interestingly, between preclinical and clinical research, translational research is benefitting from computer-based approaches, transforming the design and execution of translational research, resulting in breakthroughs for advancing human health. Accordingly, in this review article, we analyze the most advanced applications of AI in translational medicine, providing an up-to-date outlook regarding this emerging field. |
| first_indexed | 2024-03-10T03:53:28Z |
| format | Article |
| id | doaj.art-390e6b22e64f46f391203e60bd727f35 |
| institution | Directory Open Access Journal |
| issn | 2673-8937 |
| language | English |
| last_indexed | 2024-03-10T03:53:28Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Translational Medicine |
| spelling | doaj.art-390e6b22e64f46f391203e60bd727f352023-11-23T08:50:22ZengMDPI AGInternational Journal of Translational Medicine2673-89372021-11-011322328510.3390/ijtm1030016Artificial Intelligence in Translational MedicineSimone Brogi0Vincenzo Calderone1Department of Pharmacy, University of Pisa, Via Bonanno 6, 56126 Pisa, ItalyDepartment of Pharmacy, University of Pisa, Via Bonanno 6, 56126 Pisa, ItalyThe huge advancement in Internet web facilities as well as the progress in computing and algorithm development, along with current innovations regarding high-throughput techniques, enable the scientific community to gain access to biological datasets, clinical data and several databases containing billions of pieces of information concerning scientific knowledge. Consequently, during the last decade the system for managing, analyzing, processing and extrapolating information from scientific data has been considerably modified in several fields, including the medical one. As a consequence of the mentioned scenario, scientific vocabulary was enriched by novel lexicons such as machine learning (ML)/deep learning (DL) and overall artificial intelligence (AI). Beyond the terminology, these computational techniques are revolutionizing the scientific research in drug discovery pitch, from the preclinical studies to clinical investigation. Interestingly, between preclinical and clinical research, translational research is benefitting from computer-based approaches, transforming the design and execution of translational research, resulting in breakthroughs for advancing human health. Accordingly, in this review article, we analyze the most advanced applications of AI in translational medicine, providing an up-to-date outlook regarding this emerging field.https://www.mdpi.com/2673-8937/1/3/16translational medicinemachine learningartificial intelligence |
| spellingShingle | Simone Brogi Vincenzo Calderone Artificial Intelligence in Translational Medicine International Journal of Translational Medicine translational medicine machine learning artificial intelligence |
| title | Artificial Intelligence in Translational Medicine |
| title_full | Artificial Intelligence in Translational Medicine |
| title_fullStr | Artificial Intelligence in Translational Medicine |
| title_full_unstemmed | Artificial Intelligence in Translational Medicine |
| title_short | Artificial Intelligence in Translational Medicine |
| title_sort | artificial intelligence in translational medicine |
| topic | translational medicine machine learning artificial intelligence |
| url | https://www.mdpi.com/2673-8937/1/3/16 |
| work_keys_str_mv | AT simonebrogi artificialintelligenceintranslationalmedicine AT vincenzocalderone artificialintelligenceintranslationalmedicine |