Artificial Intelligence (AI) is transforming healthcare in many ways. Neural networks identify patterns and make decisions with minimal human direction. Such AI-based insights improve patient outcomes, increase healthcare efficiency, and reduce costs. Here are five ways AI is transforming healthcare.
1. Improved diagnosis
A typical clinical study produces vast datasets containing thousands of images. Test results, scans, and other medical records add to the data volume. Healthcare providers usually drown in such data and waste time hunting for patient information.
AI-powered systems supplement labour-intensive case triages. The algorithms analyse massive data sets to improve insights and make accurate diagnoses. The algorithms identify patterns and hidden relationships to make insights more effective.
AI-powered insights:
- Connect disparate data to provide a unified picture of the patient’s condition. The algorithms scour through biomedical data, electronic health records, and related sources to mine relevant and evidence-based information. The breakthrough came in 2017 when researchers at Stanford University proved AI could classify skin cancer as well as human dermatologists could.
- See patterns outside the scope of human attention. People excel in finding what they seek. But they are not too good at finding what they are not looking for. AI bridges this shortcoming and catches abnormalities that a human practitioner may miss. The AI system flags specific anomalies for a radiologist’s review. For instance, AI algorithms detect breast cancer in mammograms with a 94% accuracy rate. The algorithm identifies cancerous lesions missed by human radiologists. Such deep insights lead to earlier diagnoses and improved patient outcomes.
- Have no preconceived assumptions about findings that blind human practitioners to preconceived results.
- Speeds up diagnosis. Healthcare professionals are often overworked. When they handle too many patients, fatigue sets in, causing delays and mistakes. Worse, cases tend to pile up, leading to delayed diagnosis. AI makes diagnosis instant, saving time, which could equate to saving lives. For instance, researchers from NYU Langone Health estimate automated AI-powered analysis to find and match specific lung nodules on chest CT images 62% to 97% faster than a panel of human radiologists.
2. Better treatment
Artificial Intelligence enables new methods of treatment.
One big area is precision medicine. AI-powered systems analyse genetic information, medical history, and lifestyle factors to customise treatment plans for the patient. In cancer treatment, patients who receive such targeted therapies have a 30% higher response rate than those who receive standard treatments.
AI-assisted robotic surgery improves the accuracy and quality of medical procedures. Robots assisting orthopaedic surgeons analyse data from pre-op medical records and guide the surgeon’s instrument in real time during the procedure. Such AI-assisted surgery reduces compilations and the patients’ post-operative stay in the hospital.
AI techniques also eliminate dosage errors. Doctors determine the dosage based on general guidelines and educated guesswork. Dosing errors constitute 37% of all preventable medical errors. A 2016 study in California reveals an AI-powered mathematical formula determining the correct dose of immunosuppressant drugs for organ patients. AI techniques to predict accurate dosages are still developing but have huge potential.
AI is also making healthcare treatment proactive. The application developed by technologists at Beth Israel Medical Center is a portent of the things to come. The app predicts which patients are likely to be no-shows or suffer from relapse, enabling doctors to intervene beforehand.
3. Innovative patient care
Artificial Intelligence is also transforming patient care.
AI-powered chatbots support patients by:
- Reminding them to take medication on time
- Providing healthy eating and exercise advice
- Answering health questions.
These chatbots also schedule appointments, often automating the progress. Doctors could also use these chatbots to access patients’ medical records easily.
AI-powered virtual nursing assistants take a load off the harried human nurses. UK’s NHS and UCSF use Sensely’s “Molly.” This AI-powered nurse avatar interacts with patients, asks questions about their health, assesses their symptoms, and directs them to the most effective care setting. Such AI-powered nurse assistants could save 20% of the time nurses spend on patient maintenance tasks and saves the industry up to $20 billion annually.
Wearable devices and sensors collect data on patients’ vital signs, activity levels, and sleep patterns. AI algorithms analyse such data to identify potential health issues. This approach has already shown promise in managing diabetes, heart disease, and other chronic ailments.
4. Faster and successful drug discovery
Drug discovery is time-consuming and expensive. Traditional drug development involves extensive animal testing and clinical trials. These trials often take years to complete. Many drug candidates fail in the end because of the inability of the pharmaceutical companies to comply with the process.
AI speeds up the drug discovery process and reduces costs. AI algorithms analyse genetic information and disease pathways to predict how new drugs interact with the body. The analysis predicts success or failure and identifies side effects with lightning speed.
AI has already delivered in developing new drugs for cancer, diabetes, Alzheimer’s, and Parkinson’s.
5. More effective hospital administration
The healthcare industry is notorious for its back-office inefficiencies. 51% of a nurse’s time and 16% of a physician’s activities comprise tasks that have nothing to do with patient care. Artificial Intelligence improves hospital operations and reduces such inefficiencies.
Hospital administrators use AI algorithms to predict patient demand and optimise staffing levels. Such optimisation reduces patient wait times and improves the quality of care.
AI-based technologies, such as voice-to-text transcription, eliminate time-consuming yet essential administrative tasks. Such tasks include filling prescriptions, preparing charts, and ordering tests. Automating these applications speeds up the process and could save the industry $18 billion annually.
AI has started to play a critical role in insurance fraud detection. Insurers traditionally rely on rules and manual reviews of medical claims. AI-supported data mining searches claims for unusual patterns that suggest fraud. Insurers can investigate such red flags in greater detail. AI has the potential to save insurers $17 billion annually by improving the speed and accuracy of fraud detection.
AI improves network security as well. Healthcare facilities that use AI to detect abnormal network traffic prevent network breaches. Breaches that involve sensitive healthcare records could involve hefty fines.
For these reasons, spending on AI in healthcare will grow 48% annualised between 2017 and 2023. But it is not always smooth sailing. The biggest challenge is ensuring the accuracy and reliability of AI algorithms. AI algorithms are only as good as training data. Bias in training data causes inaccurate predictions and diagnoses. AI’s long-term success in healthcare depends on validating algorithms before application.
