Application of Artificial Intelligence in the Healthcare Industry
Introduction
The primary aim of all health-related AI applications across the board is to scrutinize the mutual interactions between all clinical methodologies and patient outcomes. AI programs are designed to attune to clinical practices such as diagnostics, pharmaceuticals, treatment protocol development, drug development, personalized medicine, patient monitoring and care.
With most industries being disrupted by the rapid uncontrolled influx of highly adaptive technologies in the Digital Age, Healthcare obviously stands to be no different. Particularly with regard to automation, machine learning (ML), and artificial intelligence (AI). All doctors, hospitals, insurance companies, and industries related to healthcare have all been part of this transitional shift – and in many cases the end results & outcomes are more positive than others. Healthcare has undoubtedly been quite substantially impacted by these new technologies however there is scope to do much more.
According to a study report about 86% of healthcare providers, life science organizations, and technology vendors are currently using artificial intelligence technology for the better. And by 2020, each of these organizations were spending an average of a whopping $54 million on AI-driven projects alone. The question remains however, what solutions were they most commonly implementing?
Here are 10 ingenious ways AI is changing the future of healthcare ( for the better)
Medical Record-keeping and Other Data Management
An important first step in healthcare systems is undeniably compiling and analyzing information (like medical records and other patient history), data management is the most widely used application of AI and digital automation in the healthcare landscape.AI programmed robots collect, store, re-format, and trace data to provide faster, more consistent access.
Repetitive Jobs
Analyzing tests, X-Rays, CT scans, data entry, and other repetitive tasks can be done faster with higher accuracy by AI powered robots. Cardiology and radiology are two key disciplines where the volume of data analysis can be time consuming. Cardiologists and radiologists in the future should only be looking at the most critical cases where human supervision is really needed.
Treatment plans
AI systems are created to analyze data – note and reports from a patient’s file, external research, and clinical expertise – to help isolate an individually customized treatment path.
Digital Consultation
AI-driven medical consultation based on patient history is nothing new. Users report their symptoms into the app, using speech recognition to compare against a database of illnesses. Offering a recommended action, that takes into account the patient's past medical history.
Virtual Nurses
Digital nurses help monitor patient conditions and follow ups with treatments, in between doctor visits. The program uses advanced ML to support & specialize in chronic illnesses.
Medication Management
The National Institutes of Health have deployed an AI powered app to monitor the use of medication by a patient. A smartphone’s webcam is partnered with AI to autonomously confirm that patients are taking their prescriptions and helps them manage their condition. Most common users could be patients with severe medical conditions, going against the doctor's advice, and participants in clinical trials.
Management of Drugs
Developing pharmaceuticals via clinical trials is highly time and resource intensive. Making this process faster and cheaper, a program powered by AI was deployed to scan existing medicines that could be redesigned to fight existing diseases.
The program found has found medications that could potentially reduce infectivity in a day, while normally such a process could take months or years at a minimum
Precision Medicine
Genetics and genomics research disease mutations link to the DNA. With AI, however, body scans can help predict and spot cancer and vascular diseases early on for some people based on their prior genetic deposition.
Monitoring
Wearable health trackers – like Fitbit, Apple, Garmin, and others – constantly monitor heart rate and activity levels. Sending in active alerts to users to get more exercise also resharing this information to doctors (via advanced AI systems) for added data points on the patient needs and habits.
System Analysis
Increasingly all healthcare invoices are going digital. As advanced AI is sifting the data to highlight errors in treatments, and workflow inefficiencies, helping healthcare systems avoid unnecessary patient hospitalizations.
Parting Thoughts
These are just the tip of the iceberg and a small sample selection of the potential including some futuristic solutions AI is currently offering to the healthcare industry. As further innovation pushes forward the emergent capabilities of advanced automation, Big Data, and combined digital workforces we. can. surely hope for more solutions in the coming years that are sustainable, save time, and significantly lower costs, with enhanced accuracy made possible.
