Integration of healthcare and machine learning has revolutionized the way patients get treatment. The healthcare industry is one of the biggest in the world, generating trillions of US dollars in revenue. According to reports from Statista, it is expected to generate revenue of US$8.36 trillion in 2025. The whole healthcare industry revolves around quality, value, and outcome, and the introduction of AI and ML in healthcare is playing a crucial role in constantly improving them.
Accelerated medical research, seamless workflows, more accurate diagnoses, quick data collection, better decision-making, and cost-effectiveness are some of the top benefits of machine learning in the medical industry. However, there are also some challenges associated with it, including algorithmic bias, data scarcity, security concerns, and others. An experienced AI/ML solutions provider can help you overcome such challenges. AI and ML have a lot of applications in healthcare that we are going to understand next.
Applications of Machine Learning in Healthcare
By far, we saw and understood the benefits and challenges related to AI and ML in medicine. The growing integration of machine learning with healthcare has shown us the revolutionized future of the medical industry. Still, it has also raised the question, "How is machine learning used in healthcare?" To understand that, we are going to look at some of the top applications of ML in healthcare.
1. Identifying Diseases and Diagnosis
Identifying diseases in their early stages has become easier than ever thanks to AI and ML. It is also considered one of the most crucial applications of machine learning in healthcare. The algorithms are trained on genetic information, patient history, medical imaging, and various anomalies to detect diabetes, cancer, cardiovascular disorders, neurological diseases, and other conditions in their early stages. There are cases where ML algorithms helped professionals predict stroke and take steps to prevent it.
2. Drug Discovery and Manufacturing
Drug discovery is crucial to withstand new or variations of existing diseases. Traditional methods of discovering drugs took a lot of resources and time. However, AI and ML integrated into healthcare have changed the game. With R&D technologies like precision medicine and next-gen sequencing, drug researchers can predict molecule interactions, identify potential drugs, and conduct tests on the disease. One of the most prominent examples of ML in drug discovery is Microsoft's Project Hangover, using AI-based technologies to create drug combinations for Acute Myeloid Leukemia.
3. Medical Imaging and Diagnostics
AI and ML in healthcare have changed the whole perspective of medical imaging and diagnostics. Techniques like CT scans, MRIs, X-rays, ultrasound, PET, SPECT, etc. require detailed observation to detect anomalies; however, sometimes, humans are not able to notice that, but that's not the case with AI/ML. They ensure detection of even the smallest irregularities, improving the diagnostic accuracy and reducing errors. According to NIH, AI trained on 5,442,907 breast ultrasound images helped radiologists reduce false positive rates by 37.3%.
4. Patient-Specific Treatment
Patients recover better and faster when the treatment plans are made addressing their needs. Healthcare professionals create such plans using AI/ML models that are trained on patients' data, like lifestyle, medical history, genetics, etc. It also ensures minimal or no side effects. For example, IBM Watson Oncology uses machine learning to offer personalized treatment to cancer patients.
5. Robot-Assisted Surgery
Robotic surgery or robot-assisted surgery is considered one of the most advanced applications of AI and ML in medicine. It helps surgeons to perform complex procedures with great precision. In cases where injuries are in tight areas or around sensitive nerves, AI identifies the best incision paths and helps doctors perform operations successfully. It can even adjust to surgeons' hand tremors and minimize the damage to surrounding tissues. ML helps surgical robots learn from previous surgeries to improve accuracy and techniques.
6. Remote Healthcare Assistance
AI and ML offer one of the best remote healthcare assistance by analyzing patterns in patients' condition, history, genetic information, and more. It is used by both doctors and patients to carefully track any type of changes in patients' conditions. AI-powered healthcare assistants like smartwatches, fitness trackers, etc, can track blood pressure, diabetes, heartbeat, etc., and send immediate alerts to your doctors if any abnormalities are detected.
7. AI/ML Treatment Suggestions
Treatment recommendations can be provided based on patients' symptoms and condition using AI and ML in the future, where it will also be used to select the dosage of medicine after monitoring various parameters such as diet, sleep, glucose level, and more. It will reduce the burden of remembering patients' specifics before recommending dosages from doctors. Such technology can also send alerts if it detects any unusual changes for further assessment.
8. Mental Health and Behavioral Analysis
According to reports from the WHO, 970 million people had a mental disorder in 2019. The number will certainly grow by 2025. Every year, about 8 million people lose the battle to mental health issues. This makes detecting mental health conditions more crucial than ever. Machine learning analyzes individuals' social media activity, speech patterns, wearable devices data, etc., to detect any signs of mental health disorders and help professionals offer necessary treatments.
9. Outbreak Prediction
We survived an epidemic, but many lives were lost too, so what if we could predict an outbreak and take necessary precautions to prevent it? It is happening now. Scientists around the world have employed AI-based technologies to monitor and predict outbreaks. They have access to website information, real-time social media updates, and large amounts of live data from satellites, which they collate and expect any type of epidemics before they happen.
10. Promoting Superior After Care and Healthy Lifestyle
Machine learning healthcare is proven to be effective when it comes to promoting superior aftercare and a healthy lifestyle. It provides timely guidance about post-treatment measures to follow. The device keeps track of the activities and nature of patients and recommends appropriate measures for better recovery and improved health conditions.
Conclusion:
AI and machine learning are changing the healthcare industry on a global scale with constant innovations and upgrades in AI/ML. With each day passing, the treatment procedures are becoming more precise. Healthcare professionals around the world are integrating AI/ML into their daily operations to provide effective treatment to their patients and help them recover quickly. ML can help you with multivariate statistical analysis, gait and motion analysis, multimodal neurochemical imaging biomarkers, biometrics, and various other day-to-day applications.
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