AI to the rescue : Importance in healthcare industry

AI is the new buzzword of the 21st century. Let it be a car manufacturing industry or pharmaceutical industry, incorporation of AI has become inevitable. Artificial intelligence plays a major role in enhancing the latest technologies in every single existing field of study. So what is Artificial intelligence? It gives machines the ability to think and make decisions without any human intervention. So, can AI outperform humans? Yes, of course, depending on the situation. A study in Moffitt Cancer Center, South Florida, revealed that trained machine learning models have an edge over humans in tracing the border of brain tumors, which is crucial before proceeding with the treatment! So, there’s no wonder if a robot performs complicated surgeries like a piece of cake!

Here are some important applications of AI in the healthcare industry:

Medical imaging and diagnostics
Drug discovery
Text analytics and NLP in healthcare
Telemedicine

1) Medical imaging and diagnostics

Have you ever noticed a doctor keenly looking at the X-Ray sheet or CT-scan sheet? Believe me that the translucent sheet carries more intricate details than Picasso’s paintings. Medical imaging is the process of imaging the interior of a body for clinical analysis and disease diagnosis. Radiology is the medical discipline that uses medical imaging to diagnose and treat diseases within the bodies of animals and humans. Medical images are generated by medical imaging techniques like X-Ray, Computerized Tomography(CT) and Magnetic Resonance Imaging(MRI). For example, an X-ray scan is analyzed for the detection of lung diseases, for diagnosis of COVID-19 CT scan is widely used nowadays!

Radiologists are special medical doctors who diagnose and treat disease by analyzing the medical images. So, how can AI contribute to radiology and medical imaging? AI can extract visual information and quantitative information from medical images and perform better data analysis. AI makes the work of radiologists easier by better interpretation of the medical images.

Machine learning is all about training algorithms to recognize patterns in the input dataset and to perform the given tasks independently. For example, machine learning algorithms can be trained to detect pneumonia from lung scans. Deep learning involves training layers of neural networks, a concept inspired by neurons in the human brain. Deep learning algorithms are widely used to reconstruct medical images and enhance image quality.

2) Drug discovery

We, humans, consume a particular substance at least in some phase of our lives, it's medicine! Do you know that it takes at least 10 to 15 years to turn one compound into a drug molecule? Drug discovery is a time-consuming process. The main purpose of drug discovery is to discover small drug molecules for a particular disease which have good efficacy and produce a good therapeutic effect. i.e., reduces the symptoms and cures the disease.

The first and foremost step in drug discovery is target identification. Drug target is a macromolecule present in the cell which causes disease. For example, the potential drug target of SARS-CoV-2 is a spike protein using which the virus enters into the cell in the body. If the spike protein is inhibited by the drug molecule, then it cannot enter into the cell, thus preventing it from causing the disease. The target molecule should be druggable. i.e., The drug target should have some binding pockets so that the drug molecule binds to it and produces desired biological response.

So, here are some ways how AI helps in optimizing and accelerating the drug discovery process

Identification of drug molecules that can bind to undruggable targets. i.e., drug targets with undefined structure.

AI creates cutting-edge drug discovery algorithms. Due to the rapid increase in processing power and reduced processing costs, the cost and time taken for the drug discovery process is reduced by many folds.

Structure prediction of drug-target molecules is vital to develop potential small drug molecules. AI aids in structure-based drug discovery by 3D structure prediction of target molecules. Alpha Fold, a deep learning model developed by the London-based AI company, DeepMind predicts the 3D structure of a protein with great accuracy and in less period. The greatest invention of the 20th century had made a breakthrough in the 50-year old protein folding problem. To know more about the protein folding problem, click here!.

AI prevents drug overdosing. It analyses electronic health records of the patients and calculates overdose risk scores which predict the risk of overdosing.

3)Text analytics and NLP in healthcare

“Hey, Siri! Turn on Bluetooth” and BOOM! The work gets done within a second. Do you know how Siri works? It uses Natural language processing and speech recognition to understand human language and process it.

Text analytics and natural language processing play a key role in deriving meaningful information from unstructured data. It converts unstructured data like a text document into structured data organized in the form of dashboards and spreadsheets. Text analytics breaks down the text document into several components. NLP analyses these components and derives useful insights for further analysis.

The amount of data generated every second is incomparably huge. In the healthcare sector, the main source of big data includes patient health records, physician notes, clinical protocols, and medical publications. It is a tedious task for humans to handle all this data manually and organize it. That’s when text analytics and NLP come to the rescue!

Here are some efficient applications of text analytics and NLP in healthcare:

The effectiveness of the medical treatment can be evaluated by text analytics. The report is generated automatically based on the onset of symptoms and cause of the disease-specific to each patient.

Patient analytics - Patient data collected from different sources are collated and the patient profile graph is created. This gives more insights into the patient’s health condition.

Identification of fraudulent insurance claims.

Chatbot is a software application that simulates human conversation via text messages or voice commands in chat. Chatbot algorithms are trained on massive healthcare data including disease symptoms, diagnostics and available treatments. It performs a variety of tasks ranging from scheduling medical appointments to providing healthcare assistance. For example, Woebot, one of the most successful chatbots provides Cognitive Behavioral Therapy, mindfulness, and Dialectical Behavior Therapy.

4) Telemedicine

Gone are the days when you had to travel to the hospital for hours and wait for your turn to consult with the doctor! COVID-19 has transformed the healthcare system drastically. Telemedicine is the new online healthcare consultant system. Telemedicine, also called e-medicine, allows healthcare providers to evaluate, diagnose and treat patients without the need for in-person visits. Vital signs of patients are monitored through mobile devices which collect data about temperature, blood sugar levels etc.

Artificial intelligence boosted the growth of telemedicine services. By evaluating large amounts of data, AI can reduce the risk of therapeutic and diagnostic errors. AI technology can be used to monitor the patient’s adherence to medication. i.e., It tracks whether the patient intakes the prescribed tablet regularly. In these pandemic times, telemedicine played a huge role in making healthcare services accessible to everyone, especially for those people who fear the risk of getting COVID-19 infection. Robotics is a cutting-edge tool in telemedicine that transforms clinical care as well as remote monitoring of patients. Robotics is especially helpful during pandemic times and prevents the further spreading of infections. Telerobots are widely used for disinfection, delivery of food and drugs, and measuring vital signs.

“AI will not replace doctors, but instead will augment them, enabling physicians to practice better medicine with greater accuracy and increased efficiency” - Benjamin Bell

This blog covers just very few applications of Artificial intelligence in the healthcare industry. AI has transformed and will continue to transform the healthcare sector, making the works of doctors and scientists easier!!

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