India’s health infrastructure began crumbling under the daily increasing cases of coronavirus. However, the daily increasing cases against a recovery rate of 97.52 percent, which is the highest in the world highlights a different picture. The problem is not the virus contraction, but the inadequate healthcare infrastructure such as beds, oxygen, ventilator, the poor ratio of doctors and nurses per patient. 

Most towns and cities are burdened and under-resourced to do swab tests for a daily surge in cases, resulting in long waiting queues for sample collection and test results. This eventually delayed the covid treatment until it reached the peak of infection, and meanwhile, their infection might have spread to others if asymptomatic or mildly symptomatic. 

In many cases, the patient with mild symptoms of the virus panicked and admitted themselves to hospitals that could have been conveniently cured at home itself with proper medication. The third wave of the pandemic created absolute chaos where the person in the critical state could not avail a bed in the hospital.

Remote healthcare in India, which remained nascent, soon gained ground in the pandemic, as doctors and patients found it convenient to keep clinic visits to a minimum. Technologies such as AI were infused in home healthtech startups that improved the speed and accuracy of diagnostics. Imaging technologies have reduced the time of diagnosis from days to seconds as cutting-edge technologies interpret, imagine, and produce instant results.

According to a joint report from EY-IPA, India’s domestic telemedicine market is estimated to reach $5.5 billion in 2020-2025 and will be growing at a compound annual growth rate (CAGR) of 31 percent.

How AI in home healthtech startups is speeding up diagnosis? 

Home healthtech startups provide cost-effective medical assistance at home that comprises services such as at-home nursing, health screening, monitoring, telemedicine, and telehealth. 

Home healthtech startups effectively leverage AI for detecting symptoms. The AI checker uses natural language processing (NLP) that analyses a patient’s free-text symptom description. After gathering information on a patient’s illness history, the machine learning algorithms assess the symptom inputs to produce care recommendations concerning the severity of a disease. For instance, an AI symptom checker can recommend self-care for mild symptoms of a disease and will advise emergency care if history shows recently being attacked with strokes, increase in high blood pressure, or heart attack.