Innovation is the prime companion of the healthcare sector in tough times. From wearable smart devices that monitor your health to Machine Learning in healthcare for personal assistance, the industry is now advancing much faster than ever before.
Google recently developed a Machine Learning algorithm to identify cancerous tumours. Stanford University is working on Machine Learning for health care to detect skin cancer.
Microsoft Project InnerEye uses AI and Machine Learning in healthcare to differentiate between tumorous and healthy anatomy with the help of 3D imagery.
Pfizer utilizes Machine Learning algorithms for researching immuno-oncology to understand the immune system’s capabilities in fighting cancer. There are countless other companies that are harnessing the power of Machine Learning healthcare research.
Machine Learning works with millions of data points together to deliver near accurate predictions. It enables healthcare professionals to provide valuable suggestions on time, assess the risk of diseases, and allocate the right resources for treatment.
One of the most important things in healthcare is quick decision making. If clinicians and healthcare providers receive more information in advance, they can minimize the risks by making treatment-related decisions beforehand.
Machine Learning for healthcare and bioinformatics can process a massive amount of data and deliver valuable insights that can help healthcare professionals in making quick decisions.
It also allows them to analyze a patient’s medical history and predict the outcomes based on their treatment and lifestyle.
On the other hand, they can also plan in advance, suggesting a comprehensive treatment to the patient, resulting in lower costs and ultimate patient experience.
Analyze medical history
- Machine Learning for the Healthcare Industry is like a blessing in disguise. There is a lot of unstructured data in the form of patient records, past treatments, and the medical history of the patient’s family.
- Machine Learning helps in analyzing the historical data of patients and supports clinicians to predict accurate conditions about their health.
- Machine Learning in healthcare allows them to extract insights from past data like diseases, family background and hereditary diseases, etc., and make quick decisions.
Identify health risks
- Another primary benefit of Machine Learning in healthcare is that by analyzing the vast amount of patient data, clinicians can identify health risks before they turn into any disease.
- Clinical facilities can use Machine Learning for health care to identify strokes from current health conditions, determine heart health, and identify other complications.
- Since Machine Learning algorithms provide real-time data and analysis, doctors and clinical professionals can diagnose potential much before.
Administrative task management
- Machine Learning for healthcare enables professionals to automate a lot of administrative tasks so that they can focus on better serving their patients.
- Machine Learning can take up the task of online appointment scheduling by smartly checking the calendar of the clinicians and allocating an appointment date.
- They can take care of billing, rescheduling appointments, filing the appointment records, sending suggestions to patients, setting up reminders, forwarding emergency calls and much more.
We have written a detailed article of the use cases of Machine Learning in different industries including healthcare. It has everything you need to know about Machine Learning. Read it here
We must not talk about Machine Learning for healthcare as the one-stop problem solver. It is a tool that complements the clinicians and assists them in delivering better outcomes.
Recently, several essential advancements in Machine Learning for the healthcare industry have taken place.
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