14 Real-World Applications of Artificial Intelligence (AI) in the Healthcare Industry

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The proliferation of new technologies in the Information Age has upended several sectors. The same applies to healthcare. Doctors, hospitals, insurance firms, and other businesses connected to healthcare have all been touched by automation, machine learning, and artificial intelligence (AI), often more favorably and significantly than other sectors. Approximately 86% of healthcare related organizations use artificial intelligence technologies. These companies will invest an average of $54 million in artificial intelligence initiatives in the coming years.

So what solutions do they most frequently use? Here are 14 ways that AI is already influencing and will continue to change healthcare.

Robotic surgery speeds up and improves the accuracy of surgical procedures. Many people fear using surgical robots in healthcare because they believe AI-powered robots can decide how a procedure should go. Robotic technology aids surgeons with more delicate and exact surgical motions; the operation is still under the supervision of a person. For instance, the Mayo Clinic in Florida employs AI-powered robots to aid in the execution of abdominal procedures and is currently developing more for brain surgery.

Many states offer their citizens healthcare claims to enable them to access medical care even when they cannot pay the high price. However, medical claims can be made fraudulently, resulting in hundreds of dollars in yearly losses. AI also resolves this issue. With AI’s automatic claim assessment, fraud can be prevented. Machine learning models with AI support can quickly evaluate, approve, and pay valid claims by identifying invalid ones. Additionally to these insurance claims, AI helps with additional fraud detections. It can uncover unpaid bills for patients and shield their personal information from theft.

Data management is the most extensively used application of artificial intelligence, and digital automation since the first step in providing healthcare is gathering and evaluating information (such as medical records and other historical data). Robots gather, archive, reformat, and track data to enable quicker, more reliable access.

Artificial intelligence systems have been developed to assess data, including notes and reports from patient files, outside research, and clinical experience, to assist in choosing the best, most personalized course of therapy.

Utilizing artificial intelligence, apps like Babylon in the UK provide medical consultations based on user medical histories and accepted medical practices. Users enter their symptoms through the app, which compares them against a database of ailments using speech recognition. After that, Babylon provides a suggested course of action while considering the user’s medical history.

AI systems relieve the need for on-call virtual nursing aides. Virtual nursing assistants might help the healthcare sector save $20 billion annually by communicating with patients and sending them to the most suitable care setting. They can monitor patients, respond to their inquiries, and provide prompt real-time responses. Most virtual nursing assistant applications available today make it possible for patients and healthcare professionals to communicate frequently and consistently. There are fewer risks of unnecessary hospital trips or readmission to the hospital as this occurs in between patient visits to their doctors’ offices. In addition to scheduling doctor visits and keeping track of patients’ health, AI-powered virtual assistants offer individualized experiences to patients and assist them in identifying their ailments based on their symptoms.

Poor Electronic Health Record (EHR) interfaces frequently cause mistakes that perplex doctors, causing them to incorrectly select the incorrect medications from drop-down choices or dose units. However, ML models may analyze EHR data using artificial intelligence and compare every patient’s new prescriptions. Doctors can evaluate and correct identified remedies that do not follow the expected trends. Consider Brigham and Women’s Hospital, which employs AI-powered software to locate and correct prescription problems.

People with significant medical conditions, patients who frequently disregard medical advice, and participants in clinical studies may be the most frequent users. The National Institutes of Health developed the AiCure app to track a patient’s medicine usage. AI and a smartphone’s webcam automatically verify that patients are taking their medications and assist them in managing their illnesses.

Clinical trial drug development can take more than ten years and cost billions of dollars. The world could alter if this process were made quicker and more affordable. Amidst the recent Ebola virus crisis, a tool powered by AI was employed to assess existing drugs that could be altered to treat the sickness. 

Heart rate and activity levels are tracked by wearable health trackers like those made by FitBit, Apple, Garmin, and other companies. They can share this information with doctors (and AI systems) for extra data points on patient requirements and behaviors, as well as alert the user to undertake more exercise.

In the Netherlands, 97% of medical bills are electronic. A Dutch startup utilizes AI to filter through the data and identify inefficient workflows, treatment errors, and patient hospitalizations that may have been avoided.

The healthcare sector might save around $18 billion due to AI applications. One use of AI in healthcare is the automation of administrative workflow. It ensures that healthcare professionals prioritize important work, allowing doctors, assistants, and nurses to spend less time on routine duties. The administrative side of healthcare can benefit from technology like voice-to-text transcriptions. They assist in automating non-patient care tasks like requesting tests, recommending drugs, and creating chart notes. AI in healthcare includes a collaboration between IBM and the Cleveland Clinic. IBM’s Watson analyses large amounts of data to help doctors provide their patients with highly customized and effective care. Additionally, medical professionals can use natural language processing to analyze thousands of medical papers (NLP).

Drugs and treatment regimens have varying effects on various patients. The potential to extend patients’ lives is immense with individualized therapy options. Personalized care is delivered via machine learning. How? It can assist in identifying the traits that suggest a patient will react a sure way to a particular course of treatment. It can forecast how likely a patient’s response to a specific treatment will be. How does the ML algorithm, though, discover this? The system gains this knowledge by comparing the treatments and results of similar patients’ data. This helps doctors create the best treatment plan possible for the patient.

Additionally, genomic research makes use of AI. Machine learning methods are increasingly incorporated into other fields, including genomic annotation and sequencing. Additionally, genome-based diagnostics employ it. Significant progress has been made in our ability to precisely and cheaply modify DNA thanks to Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), particularly the CRISPR-Cas9 system for gene editing.

By integrating more robotic technology and virtual support that improves the effectiveness of care delivery, AI-powered technology is revolutionizing healthcare. It enables clinicians to quickly create effective treatment programs for patients and early detection of contagious diseases. These are merely a few options AI is supplying to the healthcare sector. There will be additional opportunities for time savings, cost reduction, and accuracy improvement as innovation pushes the capabilities of automation and digital workforces.