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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1973 1
1975 1
1976 3
1977 2
1978 1
1979 1
1980 2
1981 1
1983 3
1984 1
1985 1
1986 5
1987 4
1988 3
1989 4
1990 5
1991 5
1992 3
1993 8
1994 8
1995 3
1996 8
1997 1
1998 8
1999 8
2000 3
2001 13
2002 7
2003 14
2004 15
2005 17
2006 17
2007 16
2008 22
2009 20
2010 31
2011 36
2012 40
2013 65
2014 72
2015 85
2016 102
2017 112
2018 186
2019 270
2020 391
2021 546
2022 694
2023 835
2024 442

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3,752 results

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Page 1
The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare.
Aung YYM, Wong DCS, Ting DSW. Aung YYM, et al. Br Med Bull. 2021 Sep 10;139(1):4-15. doi: 10.1093/bmb/ldab016. Br Med Bull. 2021. PMID: 34405854 Review.
INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. ...GROWING POINTS: AI can ultimately prove beneficial in healthcare, but requires meticulous governance similar to the governance of p …
INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including health …
Identifying drug interactions using machine learning.
Demirsoy I, Karaibrahimoglu A. Demirsoy I, et al. Adv Clin Exp Med. 2023 Aug;32(8):829-838. doi: 10.17219/acem/169852. Adv Clin Exp Med. 2023. PMID: 37589227 Free article.
Our study examined 22 notable drugs and their interactions with 841 other drugs from DrugBank. The accuracy of the machine learning approaches ranged from 68% to 78%, while the F1 scores ranged from 78% to 83%. Our study indicates that enzyme and target similarity are the …
Our study examined 22 notable drugs and their interactions with 841 other drugs from DrugBank. The accuracy of the machine learning a …
Artificial intelligence in the diagnosis and management of colorectal cancer liver metastases.
Rompianesi G, Pegoraro F, Ceresa CD, Montalti R, Troisi RI. Rompianesi G, et al. World J Gastroenterol. 2022 Jan 7;28(1):108-122. doi: 10.3748/wjg.v28.i1.108. World J Gastroenterol. 2022. PMID: 35125822 Free PMC article. Review.
In order to optimize patients' survival and quality of life, there are several unsolved challenges which must be overcome. These primarily include a timely diagnosis and the identification of reliable prognostic factors. ...The widespread digitalization of healthcare gener …
In order to optimize patients' survival and quality of life, there are several unsolved challenges which must be overcome. These primarily i …
Timing the Ischemic Stroke by Multiparametric Quantitative Magnetic Resonance Imaging.
McGarry BL, Kauppinen RA. McGarry BL, et al. In: Dehkharghani S, editor. Stroke [Internet]. Brisbane (AU): Exon Publications; 2021 Jun 18. Chapter 4. In: Dehkharghani S, editor. Stroke [Internet]. Brisbane (AU): Exon Publications; 2021 Jun 18. Chapter 4. PMID: 34279887 Free Books & Documents. Review.
Preclinical studies have shown that by combining diffusion and relaxometric MRI, timing ischemic strokes is possible with clinically acceptable accuracy. ...Exploiting advanced technologies such as Magnetic Resonance Fingerprinting (MRF), artificial intelligence (AI), and …
Preclinical studies have shown that by combining diffusion and relaxometric MRI, timing ischemic strokes is possible with clinically …
Machine Learning and Artificial Intelligence in Surgical Research.
Srinivas S, Young AJ. Srinivas S, et al. Surg Clin North Am. 2023 Apr;103(2):299-316. doi: 10.1016/j.suc.2022.11.002. Surg Clin North Am. 2023. PMID: 36948720 Review.
Machine learning, a subtype of artificial intelligence, is an emerging field of surgical research dedicated to predictive modeling. From its inception, machine learning has been of interest in medical and surgical research. ...
Machine learning, a subtype of artificial intelligence, is an emerging field of surgical research dedicated to predictive modeling. F …
Decision-Making in the Human-Machine Interface.
Falandays JB, Spevack S, Pärnamets P, Spivey M. Falandays JB, et al. Front Psychol. 2021 Feb 11;12:624111. doi: 10.3389/fpsyg.2021.624111. eCollection 2021. Front Psychol. 2021. PMID: 33643152 Free PMC article.
If our choices make us who we are, then what does that mean when these choices are made in the human-machine interface? Developing a clear understanding of how human decision making is influenced by automated systems in the environment is critical because, as human-mach …
If our choices make us who we are, then what does that mean when these choices are made in the human-machine interface? Developing a …
A review of supervised machine learning applied to ageing research.
Fabris F, Magalhães JP, Freitas AA. Fabris F, et al. Biogerontology. 2017 Apr;18(2):171-188. doi: 10.1007/s10522-017-9683-y. Epub 2017 Mar 6. Biogerontology. 2017. PMID: 28265788 Free PMC article. Review.
Many works using supervised machine learning to study the ageing process have been recently published, so it is timely to review these works, to discuss their main findings and weaknesses. In summary, the main findings of the reviewed papers are: the link between sp …
Many works using supervised machine learning to study the ageing process have been recently published, so it is timely to revi …
Decoding Nanomaterial-Biosystem Interactions through Machine Learning.
Dhoble S, Wu TH, Kenry. Dhoble S, et al. Angew Chem Int Ed Engl. 2024 Apr 15;63(16):e202318380. doi: 10.1002/anie.202318380. Epub 2024 Feb 12. Angew Chem Int Ed Engl. 2024. PMID: 38687554 Review.
Over the years, different experimental approaches coupled with computational modeling have revealed important insights into these interactions, although many outstanding questions remain unanswered. The emergence of machine learning has provided a timely and unique …
Over the years, different experimental approaches coupled with computational modeling have revealed important insights into these interactio …
Machine learning in autistic spectrum disorder behavioral research: A review and ways forward.
Thabtah F. Thabtah F. Inform Health Soc Care. 2019 Sep;44(3):278-297. doi: 10.1080/17538157.2017.1399132. Epub 2018 Feb 13. Inform Health Soc Care. 2019. PMID: 29436887 Review.
In the last few years, ASD has been investigated by social and computational intelligence scientists utilizing advanced technologies such as machine learning to improve diagnostic timing, precision, and quality. ...Machine learning techniques such as support …
In the last few years, ASD has been investigated by social and computational intelligence scientists utilizing advanced technologies such as …
Forecasting Hospital Readmissions with Machine Learning.
Michailidis P, Dimitriadou A, Papadimitriou T, Gogas P. Michailidis P, et al. Healthcare (Basel). 2022 May 25;10(6):981. doi: 10.3390/healthcare10060981. Healthcare (Basel). 2022. PMID: 35742033 Free PMC article.
In fact, the readmission rate is used in many countries as an indicator of the quality of services provided by a health institution. The ability to forecast patients' readmissions allows for timely intervention and better post-discharge strategies, preventing future life-t …
In fact, the readmission rate is used in many countries as an indicator of the quality of services provided by a health institution. The abi …
3,752 results