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 tumors. 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.
Also Read: Why use Python in Healthcare Application
Benefits of Machine Learning in Healthcare
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.
Some of the benefits of Machine Learning in Healthcare are:-
- 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.
5 Major Development Vertical of Machine Learning in Healthcare
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.
Let’s have a look at the 5 major ones that you can’t afford to miss:-
- Electronic Health Records(EHRs)
- It’s been a few years since the healthcare industry saw the development of electronic health records. These records are available in digital format, allowing different stakeholders to access them as and when needed.
- EHRs is a major advancement in Machine Learning for healthcare organizations. For example, one doctor can access the patient’s previous treatment record through the EHR system.
- The same document can be accessed by another doctor who wants to understand which treatments have worked in the past. EHRs cover a whole array of patient data and are not limited to a single aspect.
- On the other hand, EHR is the application of Machine Learning in healthcare that is done through OCR technology. Automatic document scanning takes place, and the medical data is fed into the EHR system for cross-functional access.
- These smart health records also result in saving a lot of time, money, and efforts in back office and administrative record management. The result is super-effective patient outcomes.
- Medical imaging & diagnosis
- Probably one of the most important developments in Machine Learning for health care is medical imaging and disease diagnosis. Even with all the advancements, doctors still face problems in identifying diseases.
- Machine Learning processes patient data and helps in identifying diseases that might exist in the body but are hard to identify.
- Medical imaging becomes extremely effective with Machine Learning as the algorithms can process massive tones of radiology, pathology data and make quicker decisions.
- It also enables in identifying tumours that could potentially grow in size and provide an accurate image of them so that the doctors can get a visual representation of the disease.
Read more: How HealthTech Helps to Build Cutting-edge Solutions for Patients
- Drug discovery
- Another benefit of Machine Learning in healthcare is in early-stage drug development. During this stage, pharma practitioners can utilize AI and Machine Learning in healthcare for next-generation sequencing.
- Precision medicine also benefits from Machine Learning in healthcare by finding alternative paths for treatment of complicated diseases.
- Machine Learning algorithms allow pharma manufacturers to combine medical compositions and make decisions on what works the best.
- From a large number of trials, they can collect massive data and determine which composition will turn out to be the most effective for different diseases.
- Clinical research
- There are numerous applications of Machine Learning in healthcare for clinical trials and research. Clinical research is costly and takes years to complete.
- Machine Learning assists researchers by predicting the most suitable candidates for clinical trials to minimize their chances of error. It analyzes a variety of data points like medical history, treatments, health, etc. to identify who can take part in clinical tests.
- AI and Machine Learning for healthcare organizations are beneficial in providing real-time data of candidates taking part in a study. It is an excellent way to take decisions and modify testing procedures as the predictions arise.
- Researchers often face problems in processing data and finding the next best alternative for treatment. Machine Learning models are a catalyst in processing this data and find the best paths that the researchers can follow to achieve the best test results.
- Personalized Healthcare
- With wearable smart devices becoming a prominent advancement in personal health monitoring, Machine Learning has also taken the front seat.
- Machine Learning for health care enables personal health by providing answers to common queries of patients through apps. There are Artificial Intelligence bots that can identify common queries, recognize a pattern, and forward the same to the respective doctors.
- On the other hand, by uploading health data on smart devices, patients can make better decisions for their health and change their lifestyle. Older people can also raise an emergency alarm when they need someone, which has already resulted in saving a lot of lives.
- While people are still getting used to smart devices, the benefits of Machine Learning in healthcare for such devices are plenty. Since this data is uploaded online, anyone can access this data and get to know the real-time condition of the patient’s health.
AI and Machine Learning are a boon to the healthcare world. Read here about what makes AI different from Machine Learning and Deep Learning.
Future of Machine Learning in Healthcare
Machine Learning for health care is evolving with each day. People want better healthcare outcomes, and doctors want to reduce their time and costs taken in serving each patient.
The future looks bright for Machine Learning. There could be programmed robots that would assist doctors in the surgery room. AI and Machine Learning in healthcare can enable doctors to minimize the risk during operations by going down to the minutest details of the treatment.
Machine Learning is going to expand its base in healthcare with years to come. Healthcare professionals and clinicians must start utilizing Machine Learning in their favour.
For this, you can hire BoTree Technologies and TALK TO OUR MACHINE LEARNING EXPERTS.