How is the rapid evolution of AI changing the way we manage patient care and diagnose disorders?
Artificial intelligence (AI) is no longer a novel word or concept. Its utilization, from within the automobile industry to the defense sector has been widely covered in the media. Now, the application of AI in the healthcare industry is working to kickstart a new era for health and patient care
As the years go by, we are witnessing how AI is transforming and redesigning healthcare. It is helping to resolve a number of ongoing problems experienced in the healthcare industry. The following are just a few notable ways:
Now that we know of the importance of AI in the healthcare industry, let us look at some of the applications of AI in healthcare:
The most obvious application of AI in healthcare is data management. The first step in revolutionizing the existing healthcare system is collecting, storing, and normalizing data in addition to tracing its lineage.
Integrating AI into electronic health records aids diagnostics, clinical decisions, and personalized treatment suggestions.
The use of AI in the field of cancer detection is already underway. In October 2016, IBM Watson Health announced the formation of IBM Watson Genomics, a partnership initiative with Quest Diagnostics, which aims to make strides in precision medicine by integrating cognitive computing and genomic tumor sequencing. Other major examples include Google’s DeepMind Health, which announced multiple UK-based partnerships last year, including one with Moorfields Eye Hospital in London, where they are developing the technology to address macular degeneration in aging eyes.
AI has a vital role to play in amplifying the work of drug development researchers to form essential new knowledge. The technology will help with the selection of patients for clinical trials and enable companies to identify issues with compounds much earlier in terms of efficacy and safety. It can be used to build a strong and sustainable pipeline of new medicines.
Clinical trials sometimes take more than a decade and cost billions of dollars. Speeding up these trials (which AI promises to do) and making them more cost-effective would have an enormous effect on today’s healthcare and how innovations reach everyday medicine.
Incorporating AI into radiology involves research on the development of algorithms capable of detecting differences in healthy and cancerous tissues to help improve radiation treatments. It speeds up the segmentation process (ensuring that no healthy structures are damaged) and increases the accuracy of radiotherapy planning.
The prediction of epidemic outbreaks is now possible based on data collected from satellites, historical information on the web, real-time social media updates, and other sources. For example, ProMED-mail monitors emerging diseases and provides outbreak reports in real time, using an internet-based reporting program.
AI enables the advanced ability to analyze the meaning and context of structured and unstructured data in clinical notes and reports critical to selecting a patient pathway. Then, by combining attributes from the patient’s file with clinical expertise, external research, and data, the program identifies potential treatment plans for a patient.
The world of genetics deals with huge data sets of genetic information and medical records, AI will have a huge impact in this field by identifying patterns in these massive data sets, looking for mutations and linkages to disease. A new generation of computational technologies is being used that informs doctors regarding the changes within a cell when DNA is altered by genetic variation, natural or therapeutic.
The proliferating volumes of data from patient medical history records, treatment data, and lately information from wearable health trackers and sensors could be analyzed in detail, not only to provide patients with better suggestions about lifestyle, but also to serve healthcare with defining chunks of information on how to design itself based on the needs and habits of patients.
There is definitely a place in healthcare to store and access data via a computerized system. Due to the enormous amount of data in healthcare, it promises to be the most happening sector for an AI disruption. This impending disruption will completely change the way patient care is delivered globally. AI in healthcare is already changing the way doctors are treating patients, saving money, and making treatment more efficient and tailored for each patient.
GoogleMind, IBM Watson, and many more are in the process of converging AI into the healthcare industry, which has already given some life-changing outputs. However, we are a long way away from a completely computerized system. Improving real-time decision making, aiding medical treatment, and avoiding errors are steps in the right direction, with healthcare depending on data and analytics. Although the state of “real AI” is yet to be explored and is in the budding stage, it may materialize into a fuller picture in the near future, revolutionizing the healthcare ecosystem.
Tags: healthcare industry