The influx of disruptive technologies in many industries has brought massive transformation. The healthcare industry is no different when it comes to technological intervention taking over its functioning. Particularly emerging technologies like artificial intelligence (AI), automation, machine learning, etc., have significantly impacted the healthcare sector. Even stats are indicative of the growing adaptation of AI into clinical operations. For instance, as per a recent report, it is expected that by 2020, the average spend on artificial intelligence projects is going to be $54 million.
The application of digital automation and artificial intelligence is noticeable throughout the healthcare field. From record management to providing virtual care, automation of repetitive tasks, digital consultation and accurate diagnosis, the implementation of AI is widespread.
So, what are the areas where AI application is already making a huge impact? Here is a list of the ten ways in which AI is changing the healthcare industry for a better present and advanced tomorrow.
- Enabling Next-Gen Radiology Tools
- Streamline the Use of EHR Systems
- Precise Analysis of Pathology Reports with AI
- Perform Diagnostic Duties to Meet Growing Demand of Trained Professionals
- Adding Intelligence to Smart Machines and Devices
- Extracting Actionable Insights from Wearable Devices and Apps
- Powering Predictive Analytics to Treat Complex Diseases
- Turning Selfies into Diagnostic Tool
- Machine Learning Advancing Immunotherapy Capabilities
- Brain-computer Interfaces Helping Neurological Patients to Communicate
Enabling Next-Gen Radiology Tools
Today, most of the radiological images are obtained by x-rays, MRI machines, and CT scanners. However, still, certain aspects of it depend on manual work. Practices such as the physical collection of tissue samples through biopsies continue to being done by humans which itself includes risks of infection. This is when the use of artificial intelligence comes in, enabling next-generation radiology tools that can offer more accurate and detailed analysis and also eliminate the need to collect tissue samples manually.
Artificial intelligence is driving innovation in the field of radiomics as well. It is enabling virtual biopsies that use image-based algorithms to identify the genetic properties and the phenotypes of tumors in the cancer patient. This is helping providers to better define the nature of cancer and come up with appropriate treatments that are more effective.
Streamline the Use of EHR Systems
Electronic health record (EHR) systems have been instrumental in transforming the way health records were managed, shared, and maintained by healthcare providers. However, over the course of time, EHR systems became overburdened with endless documentation, cognitive overload, user burnout, and similar other myriads of problems adding to its challenges.
However, with the integration of artificial intelligence, EHR developers are now able to create in-built interfaces and insert automation capabilities into EHRs that can save user’s time and streamline the EHR management. With the addition of features like voice recognition and dictation, the clinical documentation process has also improved tremendously. Now, with AI-backed EHR systems, clinicians can prioritize tasks and also automate routine requests like sending a notification for medication refills and test results.
Precise Analysis of Pathology Reports with AI
About 70% of healthcare decisions in the treatment of a patient is based on pathology report. Pathologists play a significant role in diagnosis by providing accurate test data based on which the physician or the nurse decides the next course of treatment.
With artificial intelligence being embedded into the pathological tools, pathologists can go deep down to the pixel level of a large digital image to identify even the nuances that the human eye may miss out. Even before a clinician reviews, the AI-driven pathology reports can save a lot of time and allow efficient screening of pathology test results.
Perform Diagnostic Duties to Meet Growing Demand of Trained Professionals
With growing healthcare demands, the availability of trained healthcare providers like radiologists and ultrasound technicians are increasing especially in the developing nations. Moreover, in certain hospitals and clinics, the few available providers are overburdened with work to fill up the increasing demand. This is where artificial intelligence has a greater and impactful role to play.
Artificial intelligence can help address the deficit of qualified and trained clinical staff by taking charge of some diagnostic duties that are usually done by humans. For instance, AI-powered tools are being used at some diagnostic centers to screen chest x-rays to find out signs of tuberculosis. This can reduce the need to have trained diagnostic professionals on site.
Adding Intelligence to Smart Machines and Devices
Smart devices are electronic gadgets with computing power that can run on the user’s command and help them in their daily activities. From car to home appliances, smart glasses, tablets, and other personal electronics, smart devices are everywhere. Just with a command, people can on/off their house lights, and this is possible all because of artificial intelligence and the internet of things (IoT).
Especially in the medical field, the possibilities and potential areas of smart device use are many. That is why smart devices backed with intelligent algorithms are proving beneficial in the monitoring of patients admitted in the ICU and other departments. Using AI, healthcare professionals can identify or sense complications, deterioration in patient condition, and use the inputs to provide proper care.
Extracting Actionable Insights from Wearable Devices and Apps
With the digital revolution, health-related data is being generated on the go. From using healthcare wearable devices that track heartbeat to tracking steps with smartphone health apps, consumers today have access to devices that help keep track of their health. This trend is progressive as more and more people take charge of their health and are aware of their health-related insights which can prevent many of the diseases and disorders right at the root.
All these health wearable devices come with sensors that collect and store valuable health data for analysis, providing a unique perspective to individual health and of the population at large. Here, artificial intelligence plays a significant role as it helps in extracting actionable insights from large volume health data sets that these devices generate. The insight collected can later be used to provide appropriate treatment and care to patients.
Powering Predictive Analytics to Treat Complex Diseases
The healthcare industry today is moving away from reactive care to predictive and proactive care. It means that healthcare providers no longer need to wait for the patient to fall sick. Thanks to predictive analytics backed by artificial intelligence that allows doctors and physicians to identify chronic diseases and complex health problems so that they can provide timely care before it’s too late.
Artificial intelligence-powered clinical decision support tools use predictive analytics to provide healthcare professionals early warning signs pertaining to conditions like seizures where timely intervention is necessary. Also in the case of coma patients, machine learning can help support decisions conclude whether or not care for such patient needs to be continued. Early alerting with data analytics support by AI holds lots of potential in making the right clinical decisions at the right time.
Turning Selfies into Diagnostic Tool
Today everyone uses smartphones ad are keen on taking Selfies. The craze for taking that perfect selfie is a popular practice among mobile users of all ages. Although for most of us, selfies are just pictures but what many doesn’t know is that smartphone images have the capacity and the quality to supplement clinical evaluation. This is proving to be beneficial for dermatology professionals who can diagnose patient’s skin problems with high-end images even from far away.
Smartphones nowadays are highly advanced with top-notch camera features and some are even backed by artificial intelligence. The images taken by these smartphones are further analyzed by artificial intelligence algorithms for better diagnosis using quality images. An algorithm can help detect nose placement, jawline and eye of the patient which can help in the efficient analysis of the patient. AI is turning smartphones into tools that can provide quality photos for analysis in clinical decision-making.
Machine Learning Advancing Immunotherapy Capabilities
Also called biological therapy, Immunotherapy is a type of cancer treatment that uses the patient’s body’s immune system to fight the cancer-causing tumor. The immune system of a human consists of organs and tissues of the lymph system and white blood cells that boost the body’s ability to fight infections and other diseases. In the treatment of cancer today, Immunotherapy is widely implemented. However, not all patients respond to immunotherapy options. And this is where the challenge begins. Finding out which patient will benefit and respond to the therapy is the key.
But with machine learning algorithms, highly complex data sets can be synthesized and analyzed to introduce new therapy options as per an individual’s unique genetic structure. This is when artificial intelligence and its associated technologies prove beneficial for the smooth functioning of treatment procedures.
Brain-computer Interfaces Helping Neurological Patients to Communicate
Earlier neurological disorders or trauma impacting the nervous system would forever take the patient’s ability to move, speak, or interact. But thanks to AI, things have changed now. Today, Brain-computer interfaces (BCIs) leveraging artificial intelligence are being used to connect computers with the human brain for restoring the condition of patient’s with strokes, ALS, spinal cord injuries, and locked-in syndrome.
To describe in simple words, a Brain-computer interface (BCI) is nothing but a collaboration between the brain and a device. With this collaboration, the interface creates a direct communication path that sends signals from the brain to an external device, allowing patients to manipulate external machinery and computers with their thoughts and express themselves which would otherwise have been impossible for people who lost control of their central nervous system.
