The healthcare system is among the most complex industries worldwide, as patients constantly demand better care management. Over the past decades, the health industry has seen its fair share of disruption due to the advent of technologies like artificial intelligence, cloud, and more. Artificial intelligence technology opens new doors in the healthcare industry by evolving its processes, operations, and workflow through an AI-driven shift.
AI in healthcare is working with an ultimate goal, i.e., improving patient outcomes by revolutionizing treatment techniques. Artificial intelligence is helping researchers make discoveries by analyzing complex medical data and drawing conclusions without the intervention of humans.
There are various subtypes of AI used in healthcare nowadays. For instance, healthcare app development companies use Natural Language Processing (NLP) algorithms to empower machines to understand and interpret human language. Similarly, Machine learning (ML) teaches computers to find patterns and make predictions based on that data.
Now, before moving forward to how AI in healthcare is transforming the industry, let’s take a look at a few statistics about the healthcare industry that you must know.
- According to a report, AI in the healthcare market will reach 67.4 billion by 2027 at a CAGR of 46.2% during the forecast period(2021-2027).
- Another report shares that 72% of healthcare leaders believe that the patient experience would be improved by predictive analysis.
- Global healthcare analytics is expected to reach $80.21 billion by 2026 at a CAGR of 27.5% during the forecast period from 2018-2025.
- Another report says that the global healthcare analytics market will reach $96.90 billion by 2030 at a CAGR of 15.3% for the forecast period(2021-2030).
AI Transforming Healthcare Industry
AI applications play a massive role in the healthcare industry, and the future of AI in healthcare looks highly promising due to the increasing use cases. Now, let’s look at how AI implementation transforms the healthcare industry.
1. Clinical Diagnoses
Artificial intelligence algorithms are programmed to detect diseases faster and more accurately than doctors. These clinal diagnoses are particularly successful in detecting diseases from image-based test results. For instance, Google’s DeepMind trained a neural network to detect over 50 eye diseases by analyzing 3D rental scans.
Similarly, AI is now used to detect cancer by scanning and analyzing biopsy images, MRI scans, and Mammography scans. It helps healthcare professionals to take preemptive measures and provide effective treatment. Even after a patient is diagnosed with a specific disease, AI systems can provide precision treatment and maintain a communication channel for better support and services.
2. Decision-making
AI-powered healthcare wearables and other medical devices track users’ health and regularly collect their health data. Healthcare organizations apply cognitive technology to analyze the vast amount of health data collected from different devices to detect any early signs of health deterioration due to bad lifestyle, genomic, or other factors.
Additionally, AI-enabled systems can review and store more medical information, including every journal, symptom, treatment history, and response time, faster than any human. It helps healthcare professionals to make trustworthy decisions with the help of AI’s timely support and predictive analytics functionality.
3. Precision treatment
Medical artificial intelligence is becoming a valuable tool for treating patients. Precision treatment or medication focuses on dispensing the correct medication, depending on the patient’s characteristics and behavior. Precision medication also involves accurate prescriptions and recovery routines necessary to get better results.
Precision treatment depends on the healthcare data such as treatment history, restrictions, hereditary traits, and lifestyle. AI tools support data-driven decision-making and offer a comprehensive approach to better disease management, care plans, and long-term treatment programs.
4. Research and training
Drug discovery is among the most crucial stages of healthcare development as it requires high precision, accuracy, and focus. Also, the path from the research lab to a patient is lengthy and costly, and it may take years and hundreds of failed attempts before a drug reaches the stage of pre-clinical testing and human testing. Big pharma research organizations are partnering with healthcare app development companies to deploy AI-powered systems that may offer benefits and uses to pharmaceutical manufacturing. These systems provide deep learning and AI algorithms to streamline the discovery and repurposing process, saving time and money.
5. Enhanced workflow
Artificial intelligence in healthcare focuses on automation by improving administrative and operational workflows. As per reports, recording and analyzing medical records in EHRs takes 34 to 55 percent of a professional’s time. NLP-based systems reduce this time, empowering healthcare professionals to focus on high-quality care. Furthermore, insurance companies are utilizing AI through linked devices to gather health data to process claims faster. It improves transparency between insured parties and companies while reducing fake claims.
6. Better lifestyle
One of the most significant benefits of AI in healthcare is the motivation to keep themselves fit among users. Artificial intelligence and the internet of medical things (IoMT) in consumer health applications are helping people develop a sense of responsibility to stay healthy, so they don’t need a doctor.
Technology applications allow users to create and maintain a healthy lifestyle keeping consumers in control of health and well-being. Moreover, AI helps professionals understand the day-to-day patterns of users, allowing them to provide supportive guidance toward health and life.
Conclusion
The future of AI in healthcare is blooming as the technology is helping health and wellness professionals take a more comprehensive approach to disease detection, prevention, and management. Although for artificial intelligence systems to develop rapidly and efficiently, data management companies must focus on churning out massive amounts of information for better results. With the advent of artificial intelligence in healthcare, it is evident that the technology is here to stay for an extended period. Though it will not replace doctors and other stakeholders, it will likely work alongside them for a longer time.