5 ways AI is transforming healthcare

• AI can analyze vast amounts of medical data to recognize patterns or spot abnormalities
• AI chatbots are being used as virtual health assistants
• AI can also help pharmaceutical scientists find promising drug molecules

In recent years, Artificial Intelligence (AI) has been transforming many industries, and healthcare is no exception. 

The application of AI technologies in healthcare has been allowing for more efficient patient care in many ways. For example, by analyzing large amounts of data and medical images in record time, AI can enable faster, more accurate diagnoses and even predict disease in some cases.

These are the five key ways that AI is changing healthcare.

1) Personalized medicine: how AI is tailoring treatments to the individual 

Personalized medicine, also known as precision medicine, is an approach to healthcare that uses the individual’s genetic makeup to determine a custom disease prevention plan or a tailored treatment with fewer adverse reactions.

AI can help in personalized medicine by analyzing patient data in search of patterns and correlations that may not be readily apparent to physicians. 

AI can interpret and generate insights from genomic data, biomarkers, medical images, and even medical records in little time, recommending prevention procedures and/or treatments that are more likely to work without complications.  

This can help improve clinical decision-making in personalized medicine.

2) Predictive analytics: how AI is enhancing healthcare outcomes

Predictive analytics is a type of data analysis that uses machine learning algorithms and statistical models to predict future events based on patterns found in historical data. 

In healthcare, predictive analytics can be used to evaluate health risks and predict diseases through the analysis of medical histories, genetic profiles, lifestyle factors, and other data sources. 

Physicians can then use this information to take more accurate preventive measures with their patients, such as proactively recommending lifestyle changes or regular screenings. For example, based on a patient’s medical or family history, it can be determined whether he or she is at a higher risk of developing diabetes. The doctor may then suggest dietary changes and regular blood sugar tests to prevent the onset of the illness or detect it early.

3) AI in drug discovery and development: a new era of efficiency

When developing new drugs, one of the first criteria is to see if the drug interacts with a specific target protein or receptor molecule. If it doesn’t meet this criterion, then it is not worth developing it further. Similarly, if it interacts with unintended proteins or receptors, it can produce undesired adverse reactions, and so would need to be altered before being developed further.

This is why it's important to estimate how well a drug will interact with its target protein or receptor through a measure called Drug Target Binding Affinity (DTBA). AI can help predict the DTBA by analyzing the features of the drug and similarities between a drug and its target protein or receptor. 

AI can also help find new drug candidates by virtually screening large databases of molecular and chemical data against a target protein or receptor. AI can simulate interactions between the target protein or receptor and thousands of drug molecules to identify the ones that could work best in clinical trials. 

By reducing the number of drug candidates for further testing and predicting outcomes, AI accelerates drug discovery and development and reduces the costs associated with them.

4) Virtual health assistants: how AI is transforming patient care

Advances in conversational AI allow virtual health assistants to communicate with patients more effectively. AI-powered virtual health assistants can ask questions, check symptoms, and collect relevant medical data and insurance details for the doctor, as well as schedule appointments and send reminders, among others.

This is important for physicians who need to focus on more specialized duties and do not have the time to handle routine tasks. By taking over the administrative part of medicine, AI can free up more time for doctors to diagnose and treat patients.

While AI can’t supplant an appointment with a human doctor or a visit to the ER if the situation demands it, AI-powered virtual health assistants can address the patient’s health concerns in an immediate way. They are designed to analyze medical data and provide custom health advice to help patients manage certain conditions. 

This way, they could help prevent complications in patients with chronic conditions that require regular monitoring or even possibly save the lives of patients who live in remote areas and can’t get to the hospital right away.

5) AI and medical imaging: the future of diagnostics

Medical imaging, such as X-rays, computerized tomography (CT) scans, magnetic resonance imaging (MRI), and ultrasounds, are all important tools for diagnosing and monitoring a number of different health conditions. But the interpretation of medical images can be time-consuming, and the quality can be variable among different healthcare providers.

AI-based algorithms can analyze large amounts of imaging data and identify patterns and abnormalities more quickly and, sometimes, even more accurately than human clinicians. For example, they can compare several images and detect subtle changes that would go unnoticed by human doctors, and that would perhaps indicate that the person is developing cancer, cardiovascular disease, or other life-threatening conditions.

This can lead to faster diagnoses or earlier detection of disease, which can be essential to make treatment more effective and save lives.

AI algorithms can also evaluate medical images and classify them, prioritizing the ones that require more urgent attention and the ones that may be of lower concern. This automation of the triage process can help optimize the use of imaging resources and reduce wait times for patients. 

In spite of all these benefits, AI isn’t perfect. It can make errors, so it needs to be supervised. And most importantly, it lacks the skills of human interaction and cannot replace human judgment. Due to this, AI isn’t likely to supplant human doctors any time soon – but it is likely to keep helping them in more and more medical tasks, as it has already shown that it is capable of delivering solutions to aid in the detection, prevention, and treatment of illness.