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The Use of Artificial Intelligence in Medicine: Present and Future – Part II

Dr. Meenakshi Bhattacharjee Rice University, Houston TX

Dr. Meenakshi Bhattacharjee
Rice University, Houston TX

by Meenakshi Bhattacharjee
Health assistance and medication management:
Welcome the world’s first virtual nurse. Molly was developed by the medical start-up Sense.ly. It has a smiling, amicable face coupled with a pleasant voice and its exclusive goal is to help people with monitoring their condition and treatment. The interface uses machine learning to support patients with chronic conditions in-between doctor’s visits. It provides proven, customized monitoring and follow-up care, with a strong focus on chronic diseases. Also, there is already a solution for monitoring whether patients are taking their medications for real. The AiCure app supported by The National Institutes of Health uses a smartphone’s webcam and AI to autonomously confirm that patients are adhering to their prescriptions, or with better terms, supporting them to make sure they know how to manage their condition. This is very useful for people with serious medical conditions, for patients who tend to go against the doctor’s advice and participants in clinical trials.
Precision medicine
Artificial intelligence will have a huge impact on genetics and genomics as well. Deep Genomics aims at identifying patterns in huge data sets of genetic information and medical records, looking for mutations and linkages to disease. They are inventing a new generation of computational technologies that can tell doctors what will happen within a cell when DNA is altered by genetic variation, whether natural or therapeutic.The whole process enables to spot cancer or vascular diseases in their very early stage.
Drug creation:
Developing pharmaceuticals through clinical trials take sometimes more than a decade and costs billions of dollars. Speeding this up and making more cost-effective would have an enormous effect on today’s healthcare and how innovations reach everyday medicine. Atomwise uses supercomputers that root out therapies from a database of molecular structures. Last year, Atomwise launched a virtual search for safe, existing medicines that could be redesigned to treat the Ebola virus. They found two drugs predicted by the company’s AI technology which may significantly reduce Ebola infectivity. This analysis, which typically would have taken months or years, was completed in less than one day. Another great example for using big data for patient management is Berg Health, a Boston-based biopharma company, which mines data to find out why some people survive diseases and thus improve current treatment or create new therapies. They combine AI with the patients’ own biological data to map out the differences between healthy and disease-friendly environments and help in the discovery and development of drugs, diagnostics and healthcare applications.
Open AI helping people make healthier choices and decisions
Open AI ecosystem is a new and a very fancy expression for connected AI infrastructures. However, the World Economic Forum named it as one of the top 10 emerging technologies in 2016, so it might be worth getting familiar with it. An open AI ecosystem refers to the idea that with an unprecedented amount of data available, combined with advances in natural language processing and social awareness algorithms, applications of AI will become increasingly more useful to consumers. It is especially true in the case of medicine and healthcare. There is so much data to utilize: patient medical history records, treatment data – and lately information coming from wearable health trackers and sensors. This huge amount of data could be analyzed in details not only to provide patients who want to be proactive with better suggestions about lifestyle, but it could also serve healthcare with instructive pieces of information about how to design healthcare based on the needs and habits of patients.
Analyzing a healthcare system
97% of healthcare invoices in the Netherlands are digital containing data regarding the treatment, the doctor and the hospital. These invoices could be easily retrieved. A local company, Zorgprisma Publiek analyzes the invoices and uses IBM Watson in the cloud to mine the data. They can tell if a doctor, clinic or hospital makes mistakes repetitively in treating a certain type of condition in order to help them improve and avoid unnecessary hospitalizations of patients.
AI surgical robots
Google has struck a deal with the healthcare company Johnson & Johnson to develop surgical robots that use artificial intelligence. The robots will aid surgeons in minimally invasive operations, giving operators greater control and accuracy than is possible by hand, minimizing trauma and damage to the patient. Some systems allow surgeons to remotely control devices inside the patient’s body to minimize entry wounds and reduce blood loss and scarring.Robotic surgical systems such as the Da Vinci device developed by Imperial College London have been used in general operations since the early 2000s.
What do we need to take AI applications to the next level?
First and foremost, we have to tear down the prejudices and fears regarding artificial intelligence and help the general population understand how AI could be beneficial and how we can fight its possible dangers. The biggest fear is that AI will become so sophisticated that it will work better than the human brain and after a while it will aim to take control over our lives. The development of full artificial intelligence could spell the end of the human race.
We need the following preparations to avoid the pitfalls of the utilization of AI:
1. Creation of ethical standards which are applicable to and obligatory for the whole healthcare sector
2. Gradual development of AI in order to give some time for mapping of the possible downsides
3. For medical professionals: acquirement of basic knowledge about how AI works in a medical setting in order to understand how such solutions might help them in their everyday job
4. For patients: getting accustomed to artificial intelligence and discovering its benefits for themselves – e.g. with the help of Cognitoys which support the cognitive development of small children with the help of AI in a fun and gentle way or with such services as Siri.
5. For companies developing AI solutions (such as IBM): even more communication towards the general public about the potential advantages and risks of using AI in medicine.
6. For decision-makers at healthcare institutions: doing all the necessary steps to be able to measure the success and the effectiveness of the system. It is also important to push companies towards offering affordable AI-solutions, since it is the only way to bring the promise of science fiction into reality and turn AI into the stethoscope of the 21st century.
If one succeeds, huge medical discoveries and treatment breakthroughs will dominate the news not from time to time, but several times a day.


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