Google introduced that it’s funding 15 AI-powered initiatives, together with digital well being initiatives to enhance supplier expertise and affected person entry to care, by way of its dedication to advancing the United Nations Sustainable Development Goals.
Every venture obtained $3 million in technical help, money help and Google Cloud credit. A handful of initiatives obtained Google.org Fellowships, the place a crew of Google staff works with a corporation professional bono full time for as much as six months.
Of the 15 AI initiatives funded, the next eight digital well being endeavors had been awarded funding:
RAD-AID gives low-source hospitals with an AI-enabled platform that helps triage sufferers, primarily concerning respiratory illness and breast most cancers. The platform additionally helps interpret X-rays and scans and supply take a look at outcomes.
Wuqu’ Kawoq and secure+natal are collaborating to develop a machine learning-enabled instrument package to assist midwives in rural areas of Guatemala detect neonatal issues in real-time, similar to poor fetal development and fetal stress throughout supply. The instrument package will include an ultrasound and blood stress monitor linked to 1’s smartphone.
MATCH (Music Attuned Know-how – Care by way of eHealth) is a venture constructed out of the College of Melbourne and CSIRO that mixes music and wearable sensor know-how to lower agitation in sufferers with dementia. Google’s grant will assist the crew develop the sensor know-how and AI-enabled adaptive music system.
Makerere AI Lab will develop a 3D-printed adapter that processes photos utilizing AI and is suitable with a telephone or microscope. The objective is to assist suppliers in Uganda diagnose sufferers with sicknesses, similar to tuberculosis, malaria and most cancers in low- and middle-income nations the place lab technicians are scarce.
IDinsight with Attain Digital Well being developed a pure language-enabled question-answering service for expectant moms in South Africa, which gives solutions to inquiries and very important well being info.
Causal Foundry seeks to develop a smartphone-based instrument that makes use of machine studying to assist neighborhood well being suppliers in Sub-Saharan Africa handle affected person info and conduct modifications associated to being pregnant and childbirth.
Jacaranda Well being delivers an SMS-based digital well being platform that solutions questions for expectant moms in Sub-Saharan Africa. The platform gives behavioral nudges and features a pure language-powered assist desk that helps triage sufferers and join them to human brokers. The funding will probably be used to refine the machine studying mannequin throughout the platform.
The College of Surrey and Signapse will use generative AI to translate on-line and offline textual content in actual time for deaf folks within the U.S. and U.Okay. and supply photorealistic movies in signal language, allowing extra accessible entry to healthcare and different info.
THE LARGER TREND
Google has its personal machine studying know-how, dubbed Med-PaLM 2, geared toward enhancing healthcare info entry. Med-PaLM 2 makes use of the tech firm’s massive language mannequin to reply medical questions.
In March, Med-PaLM 2 was tested on U.S. Medical Licensing Examination-style questions and carried out at an “knowledgeable” test-taker degree with 85%+ accuracy. It additionally obtained a passing rating on the MedMCQA dataset, a multiple-choice dataset designed to deal with real-world medical entrance examination questions.
One month later, Google introduced it could make Med-PaLM 2 accessible to pick Google Cloud clients to discover use circumstances, share suggestions and for restricted testing.
The corporate additionally announced a brand new AI-enabled Claims Acceleration Suite, created to assist with the method of prior authorization and claims processing in medical insurance. The suite converts unstructured knowledge (datasets not organized in a predefined method) into structured knowledge (datasets extremely organized and simply decipherable).
In July, a examine carried out by Google researchers and revealed in Nature revealed that Med-PaLM supplied long-form solutions aligned with scientific consensus on 92.6% of questions submitted, which aligns with clinician-generated solutions at 92.9%.
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