Top 7 Examples of Machine Learning Automates Healthcare Industry

In this article, we have discussed the best examples of how machine learning can help automate your healthcare software development business processes.

Machine learning is used in finance and education. New technology is transforming healthcare. 69% or more of medical institutions say AI has improved efficiency. AI helps with administrative activities like appointment scheduling, medical record administration, and surgical support.

This article discusses the benefits of medical technology and AI in healthcare. Learn how to use AI in healthcare.

Machine Learning and AI in Healthcare?

Before exploring how AI transforms healthcare, let’s review machine learning for healthcare. Machine learning, a type of AI that allows machines to process health data automatically, enables intelligent computer systems to replicate human behavior. These technologies utilize algorithms to increase data sets to improve accuracy and performance.

Machine learning is used in logistics, banking, manufacturing, retail and customer service, business, cybersecurity, blockchain development company, genetics, and education. 48% of companies use machine learning, per Earth Web. The medical industry is rapidly embracing new technologies to improve therapy.

The healthcare business uses machine learning to analyze massive volumes of daily data and identify trends and insights. Humans can’t do this, but AI can. Machine learning can automate medical billing, aid decision-making, and create clinical practice standards.

Benefits of Using AI in Healthcare

This section discusses AI’s benefits because it has already transformed many fields, including healthcare.

AI can improve patient outcomes, cut expenses, and simplify staff duties. The benefits of identifying diseases and monitoring persons at high risk are clear. AI and ML can benefit healthcare in many ways. Examples:

Improved Patient Experience

Machine learning in healthcare allows for more personalized care, such as appointment and medication reminders. AI could combine data sources to create a complete picture of each patient’s health and therapy recommendations.

Cost Cuts

The healthcare business loses billions of dollars yearly on useless tests, treatments, and procedures due to human error and poor communication. Medical machine learning can eliminate errors by offering precise results based on physician and patient criteria.

This is true for those who have tests or surgery often. AI-driven systems help track patients’ medical information across many locations, preventing them from starting from scratch each time they visit a different doctor or hospital. Less duplication and errors result in cost savings for both parties.

Patient Outcomes Improvement

AI and machine learning can be used in healthcare to discover data trends and patterns, helping doctors make more accurate diagnoses and treatment plans. We can improve patient outcomes and save money by reducing unnecessary drugs and hospital stays.

AI can help clinicians determine the best course of treatment for each patient based on their medical history and symptoms. This ensures immediate medical care for all.

Access to Healthcare

AI solutions allow patients to quickly and easily access their medical information by offering safe Internet or mobile access. This allows people to get health-related answers without visiting a doctor or hospital. AI will allow doctors to engage remotely with patients and undertake virtual exams, expanding their reach.

Increased Employee Satisfaction

AI and machine learning can reduce worker burdens by automating repetitive tasks. Specialists can now focus on patient care. Once medical records are digitized, and on the cloud, doctors and other employees can access them from anywhere. Less time spent on administrative tasks like data entry frees up time for patient care and education.

Eliminating repetitive jobs that don’t require their knowledge enhances employee morale. AI provides consumers with real-time data, reducing human error and improving healthcare quality.

Best Examples of Machine Learning in the Healthcare Industry

AI could improve patient outcomes in five ways, from early disease prediction to better treatment outcomes. Healthcare expenditures and staff fatigue are the industry’s biggest issues. Higher regulation requires personnel to spend more time processing electronic health records (EHR). AI automation in healthcare can reduce time- and resource-intensive jobs, freeing up people for more vital work.

Data, analytics, and innovation have helped improve healthcare. What is machine learning in healthcare? Seven real-world examples are listed.

1.  Telemedicine

Rising patient numbers have overworked nurses. Virtual nurses are one AI healthcare application that overcomes this problem. These computer-generated avatars support patients like humans. Nurses are available 24 hours a day, seven days a week, to give rapid, thorough responses between medical appointments.

Sense.ly made virtual nurse Molly. The program allows patients and doctors to communicate quickly and effectively from anywhere and at any time. Voice recognition technology gathers medical data and remotely analyses health. Molly schedules doctor appointments and collects patient weight, temperature, and blood pressure.

2.  Healthcare Imaging

Medical imaging involves monitoring the human body to diagnose and treat diseases. Machine learning algorithms can estimate leukemia recurrence rates and diagnose malignant tumors 90% more accurately. Technology can detect more problems than humans.

AI and machine learning can check scanned photos for flaws. This ensures proper treatment and diagnostics. Imago Systems illustrates medical imaging. They’re organizing images to make it easier to see irregularities that may signify sickness.

3.  Robotic Surgery

AI and machine learning robots can streamline surgical processes by cutting and stitching. They’re more precise and intrusive. Tremors or accidental movements during surgery can be disastrous, even for competent surgeons. AI and robotics must be used in healthcare to aid doctors and improve surgical outcomes.

Senhance Surgical System is an AI surgical robot. This system includes RC firearms. This software uses machine learning and deep learning to automatically simulate procedures and change the camera’s angle.

4.  Pharmaceuticals

During the Covid-19 outbreak, AI helped create vaccines. AI, ML, and deep learning are great for beginning and testing novel medicines because it’s expensive, time-consuming, and labor-intensive. These technologies accelerate and minimize the cost of medication development by analyzing large amounts of data.

U.S. pharmaceutical and biotechnology company Pfizer is an example. Pfizer uses IBM Watson for oncology research. This computer technology can predict future outcomes and automate laborious operations. This machine can analyze 4 million patient records and 1 million pieces of medical evidence in a year, while a person can only read 300 papers concurrently. IBM Watson helps Pfizer manufacture drugs more quickly based on information on active components and how they affect the body, which is critical during epidemics.

5.  Analysis of Patient Data

AI helps medical institutions analyze clinical data and understand patient health. Doctors use machine learning and a list of key information to collect data quickly. The ML program solicits patient feedback based on this list, facilitating information acquisition, cost reduction, and resource optimization.

Zakipoint analyses medical data. It displays health data on a dashboard to identify dangers, provide individualized treatment options, and improve clinical outcomes.

6.  Outbreak Prediction of Disease

Health institutions can utilize artificial neural networks to detect and predict disease outbreaks. The Ebola outbreak in West Africa shows how AI could help healthcare. Google researchers used AI to indicate an increase in Ebola cases in Liberia three months before the eruption. Researchers used the same technology to detect swine flu and influenza before they become pandemic.

7.  Hospital Management

AI also manages hospital administrative duties, optimizes resources, and analyses data. Staff scheduling is based on employee availability and workload, which is relatively easy for human managers.

AI in hospitals? They help control patient flow and prevent overcrowding by recognizing which patients need treatment first based on their symptoms. The algorithm may also analyze if extra people or beds are required based on the emergency department’s current patient load and the number of patients seen since the last shift change.

Final Briefing

This essay discusses the use of AI and machine learning in healthcare software development companies and their possible benefits. Virtual nursing, medical imaging, robotic surgery, drug research, patient data analytics, disease prediction, and hospital management use AI. Using AI and ML, you may build automated health systems for your organization’s resource- and cost-intensive procedures. This is a reliable answer, but these technologies only work when used.