AI News, Artificial Intelligence key to Universal Health Coverage artificial intelligence
- On Saturday, January 5, 2019
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Artificial Intelligence and Global Challenges — A plan for progress
Goal nº 3: “Good Health and Well-Being for People: Ensure healthy lives and promote well-being for all at all ages.” How Artificial Intelligence technologies can play a central role in the achievement of the Sustainable Development Goals one by one.
To ensure healthy lives and promote well-being for all at all ages, this UN goal is broad and has several fronts: reduce mortality rates, end epidemics, increase disease prevention, ensure access to sex education, achieve universal health coverage, support vaccine development and improve training of health professionals in developing countries.
Big data and artificial intelligence can open a precedent for remote care and mobile health to significantly change the practice of medicine and create new forms of medical care.
One of the key targets of SDG number 3 is by 2030, reduce the global maternal mortality ratio to less than 70 per 100.000 live births.
As the main causes of maternal mortality today are still hemorrhages, infections, complications related to unsafe abortions and pregnancy-related hypertension, most of those deaths could be avoided.
PeriWatch notifies clinicians about patients whose conditions are worsening, it uses an AI based approach to continuously analyze fetal heart rate, contractions, labor progression, provides maternal vital sign alerts.
It includes the reduction of neonatal mortality to as low as 12 per 1.000 live births and under 5 mortality to as low as 25 per the same ratio.
This data presents a scenario of approximately 7.000 neonatal deaths everyday — 2 million of those deaths occurred between the first day of birth and the sixth day of life.
This instant identification allows health care professionals to take quick action to prevent death and various disabilities such as cerebral palsy, deafness and muscle paralysis.
When talking about preventing death of children under 5 years old, the current data provided by UNICEF, shows us a scenario where one in 26 children still die before reaching this age.
Notwithstanding the progress made so far in reducing child mortality over the past few decades, an estimated 5.4 million children under age 5 died in 2017 — roughly half of those deaths happened in sub-Saharan Africa.
Mortality rates among older children and young adolescents (aged 5–14) plunged by more than 50 per cent since 1990, however almost one million children died in this age group in 2017 alone.
The Sustainable Development Goals are interconnected and extend the mapping potential with AI technologies, big data and satellite images for target regions where children are most vulnerable to dying from disease can also be a great way to tailor appropriate interventions.
Every day in 2017, about 4.900 people were newly infected with HIV and nearly 2.580 people died from its related causes, mostly because of inadequate access to prevention, care and treatment services.
When talking about artificial intelligence and its potential to end the epidemic of AIDS we see researchers working on developing vaccines and advanced treatments and diagnosis using machine learning.
The tool is accessible for free throughout the EU, and hits into data from across both Europe and Africa to discover the right combination of drugs that provides resistance for the maximum amount of time.
According to a publication in the journal Scientific Reports, scientists have found that the triclosan, a component already used in products such as laundry soap, toothpaste, furniture and clothing can aid in the treatment of malaria.
With the help of a robot called Eve, it was discovered that the triclosan can inhibit the enzyme of two different parasite species that causes the disease including its variants and that might lead to the development of new medications.
This platform has already been used in Malaysia and Brazil and works by combining epidemiological research (with public health data and weather forecasting) and AI to predict outbreaks of these diseases in urban settings.
The accuracy index of the analysis in Rio de Janeiro was 84.11% where it was possible to predict up to 3 months in advance the sites that would have a higher incidence of the diseases, which helped guide the preventive work to effectively fight the virus.
From improved timeliness and accuracy in diagnosis to simplified disease monitoring and surveillance, AI enables quick responses in emergencies as a fundamental in distance and adapted learning.
With the evolution of science and the potential of big data being explored for automated diagnostics and more accurate results, health entered the era of the 4th industrial revolution, we simply need to make sure it arrives for us all.
- On Friday, October 18, 2019
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