The ongoing Covid pandemic has changed the world profoundly. And this public health crisis has again put technology in sharper focus in the health care sector. As this pandemic is still amidst us and the vaccine has rolled out, the combination of IoT (Internet of Thing) and AI (Artificial Intelligence) applications can be employed to maintain social distancing and contactless touch in the healthcare sphere. IoT is so pervasive that no sector is untouched by it. But the actual value of deploying IoT is the analysis of the data generated from it to make specific applications. In that sense, a synergy between IoT and AI can unleash transformative potential in the healthcare sector.
AI performs tasks that usually need human intelligence, such as visual perception, speech recognition, decision-making, and language translation. In the health care context, AI can perform simple tasks such as answering the phone to complex tasks such as reviewing the medical record, analysing population health trends, to inventing new therapeutic drugs and vaccines. As AGI (Artificial general intelligence) is in a nascent stage, only ANI (Artificial Narrow Intelligence) is employed in patient-oriented, clinician-oriented, and administrative and operational-oriented applications.
IoT and AI applications can transform all the components of the healthcare ecosystem, such as pharmaceutical companies, health insurance companies, and hospitals. For the pharmaceutical industry, AI can streamline clinical trials and speedily discover new drugs and vaccines. For health insurance companies, AI will not only detect false claims but also speed up the claim process.
For hospital administration, AI will bring out efficiency and improve health outcomes. For Nurses, AI will set them free from spending time on regulatory and routine administrative tasks and allow them to focus more on the patient’s treatment. AI applications can create social distancing within the hospital periphery at the OPD (Out Patient Department), laboratories, pharmacy, and the patient wards.
Thanks to AI, the health care provider can stratify the need of patients and prioritise emergency care. And depending upon the severity of the patient’s health condition, IoT and AI applications enable care providers to provide care at home or the hospitals. For instant geriatric patients and patients with chronic illness can use Virtual Health Assistants (VHAs) and wearable’s, which regularly monitor the vitals of the patient’s such as blood glucose, oxygen, pulse rate, breath, and temperature. And in case of specific need arise it sends real-time update though cloud which enables health provider to initiate various health interventions. Automation in hospital tasks using AI is handy in patient self-care, allowing the patients to schedule their appointments, paying bills, and filling out or updating forms all at their convenience. Hospitals can reduce cost, patient waiting times and increased better health output. Chabot uses NLP, concept extraction, and sentiment analysis technologies to create an interactive experience, enhance patient satisfaction and produce better health output.
Natural language processing applications employ statistical and semantic NLP such as speech recognition, text analysis, translation to convert unstructured data (spoken words/dictated speech) into structured codified data usable by a computer application. NLP enables clinicians to create a complete EHP (Electronic health profile) of a patient. Thanks to the development of more intelligent, electronic health record (EHR), health information exchange (HIE) systems, and processing public health data from various sources, AI can predict the future public health crisis and can prevent it.
Thanks to new cognitive computing technologies, ML not only solves NLP tasks but also effectively collects and accurately analyse massive data generated from various sources such as research and development, patient records, and wearable’s(smartwatches and exercise trackers).
Compared to the previous generation of automated tools such as CAD (computer-aided detection), Radionics and deep learning can give far superior accuracy to detect potential lung cancer and breast cancer lesions in radiology images. Designing treatment plans in oncology is often complex and time-consuming as it needs to protect the surrounding healthy tissue when targeting cancerous cells. AI provides a more effective treatment plan within minutes for the cancer patient. With the help of ML and NLP, the oncologist can read and assimilate current information to provide the latest treatment to the patients.
Although surgical robots are deployed in the surgical procedure, the industrial robot has been used to provide medical and food supplies to the patient and conduct fogging in public places and hospital premises during the pandemic in China. Furthermore, drones are used to provide emergency supplies (medicine and food) to the hospital.
One of the challenges across the globe was to screen the incoming passengers at the airport with fever without coming in close contact with them. With the partnership with Sensei Tech and System Level Solutions, HEALTHie ShieLD has come with an innovative risk-free solution to check a person’s fever status via temperature. This application is handy to check persons with fever at the airport terminal, railway stations, bus stations, mall, religious places, theatres, auditorium, educational institutes, factories, plants, and offices.
Although IoT and AI have been sporadically used in the healthcare sector for the last decade, the recent outbreak of the Covid pandemic has accelerated its process to integrate into the healthcare sector.