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By Hannah Mitchell for Becker’s Hospital Review
Artificial intelligence‘s role in healthcare is growing and has the potential to mitigate common difficulties in the industry.
The following artificial intelligence articles were published by Becker’s Hospital Review this week:
- AI can use wireless signals to reduce errors in self-administered medication
Errors in self-administered medication can be mitigated by a new artificial intelligence tool that can monitor wireless signals in a patient’s home, according to a March 18 study published in Nature Medicine.
- Sharecare develops machine learning model to predict allergy flare-ups
Digital health company Sharecare developed and trained a machine-learning algorithm to forecast environmental allergies using smartphone and geolocation data, according to a March 23 news release.
- New AI tool being tested in UF Health study to improve Parkison’s diagnosis
University of Florida researchers will test an artificial intelligence tool to improve diagnosis for early cases of Parkinson’s disease.
- FDA authorizes 1st machine learning COVID-19 screening tool
The FDA authorized the first machine learning COVID-19 screening tool for emergency use to identify COVID-19-related health conditions in asymptomatic patients, according to a March 19 news release.
- AI tool uses EHR data mining to support diagnostic decision-making
Data mining has the ability to reduce costs and errors in diagnostic analysis. When paired with EHRs, it can be used to support physicians with diagnostic decision-making, according to a March 9 report published in the Journal of Biomedical Informatics.
- Machine learning tool can predict severe illness, death from COVID-19 in patients
Researchers developed a machine learning calculator that provides predictions of whether patients hospitalized with COVID-19 will progress to severe illness or death, according to a March 2 study published in Annals of Internal Medicine.
- New machine learning tool can accelerate drug discovery
Machine learning can quickly and precisely evaluate binding free energy used in drug discovery, according to a March 15 study published in The Journal of Physical Chemistry Letters.
- Study: Machine learning can help detect cancer cells by their acidity
Machine learning could be used in pH imaging to detect single cancer cells based on their pH levels, according to a March 16 report published in AIP Publishing.
- Machine learning could use EHRs to predict suicide risk
Machine learning could use real-time predictive models to assess suicide attempt risk in nonpsychiatric settings in a large clinical system, according to a March 12 study published in JAMA Network Open.