After revolutionizing various industry sectors, the introduction of artificial intelligence in healthcare is transforming how we diagnose and treat critical disorders. A team of experts in the Laboratory for Respiratory Diseases at the Catholic University of Leuven, Belgium, trained an AI-based computer algorithm using good quality data. Dr. Marko Topalovic, a postdoctoral researcher in the team, announced that AI was found to be more consistent and accurate in interpreting respiratory test results and in suggesting diagnoses, as compared to lung specialists. Likewise, Artificial Intelligence Research Centre for Neurological Disorders at the Beijing Tiantan Hospital and a research team from the Capital Medical University developed the BioMind AI system, which correctly diagnosed brain tumor in 87% of 225 cases in about 15 minutes, whereas the results of a team of 15 senior doctors displayed only 66% accuracy. With further improvements and the support of other advanced technologies like machine learning, AI is getting smarter with time.
Artificial intelligence in healthcare has come a long way. The use of computers has advanced significantly over the past few years. Today, sophisticated machines have been developed to perform human tasks like analyzing and interpreting data and assisting with problem-solving. While machine learning (ML) has been widely used in many industries, the use and application of Artificial Intelligence (AI) in healthcare is still relatively new. It is only recently that we have seen AI move from the world of academics and research laboratories to hospitals.
Using common social media platforms like Twitter and Facebook, healthcare professionals (HCPs) are able to share more about their practices and start-up companies to reach patients, investors and other HCPs. When it comes to communicating with companies, social media allows for a stronger reciprocal relationship between the user and the provider, due to the greater level of engagement and interaction. Social media also provides a useful tool for patients and how they approach health-related issues they're more reticent to openly discuss with their doctor, such as mental health. Tumblr has become a well-regarded outlet for discussion-oriented blogging around mental health issues. Respected organizations and individuals like National Alliance on Mental Illness (NAMI) or New York City's first lady Chirlane McCray, are engaging with Tumblr users discussing mental health topics through a dedicated space, making it easier for people to engage.
Applying the same technologies used for voice recognition and credit card fraud detection to medical treatments could cut healthcare costs and improve patient outcomes by almost 50%, according to new research. The research by Indiana University found that using patient data with machine-learning algorithms can drastically improve both the cost and quality of healthcare through simulation modeling. The computer models simulated numerous alternative treatment paths out into the future and continually planned and replanned treatment as new information became available. In other words, it can "think like a doctor," according to the university. This is not the first time artificial intelligence has been brought to bear on healthcare.
Famous social media influencer Gary Vayernurchuk says, "The future belongs to Voice." Look at all AI (artificial intelligence) driven assistants around us, from Alexa to Google Assistant, there is inherent convenience in just saying it out loud and having voice based conversations with your'virtual' assistant rather than writing commands or selecting a drop down menu. We all know that healthcare needs to be digitised in order to reach the next level of patient care. Technologies like AI and Blockchain need to be integrated into existing healthcare systems in order to make them more efficient. But these technologies can only work if all our processes are digitised first.