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Article: Connecting the dots: Technology, healthcare, and pandemics like COVID-19 | OpEdNews

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Article: Connecting the dots: Technology, healthcare, and pandemics like COVID-19 | OpEdNews
Prof Rishi Sethi, senior cardiologist from India and Amit Khare from US were keynote speakers for #SDGtalks on artificial intelligence and machine learning based solutions for healthcare problems
Prof Rishi Sethi, senior cardiologist from India and Amit Khare from US were keynote speakers for #SDGtalks on artificial intelligence and machine learning based solutions for healthcare problems
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Technology is often seen as a bane that impedes human ability rather
than benefit it. We have seen the cost of our advancement in the increasing
rates of deforestation, the rise of global warming and the absolute
carelessness with which we treat nature. The increase in awareness has led to
people becoming more environmentally conscious, yet, understandably, we cannot
compromise the development of countries as technology keeps advancing. And in
the same way, we cannot cause any more degradation to the environment for the
advancement of technology or development. However, in light of recent events,
it is perhaps the technology that will help us emerge from the pandemic
unscathed to a more considerable extent. The Guardian recently reported that
this destruction of the environment is causing pathogens to reduce boundaries
between humans and animals.

In the Sustainable Development e-Talks (#SDGtalks) series, hosted by
Indian Institute of Management Indore and CNS, Professor (Dr) Rishi Sethi, a
noted cardiologist and biomedical researcher and Amit Khare, the co-founder and
CEO of Evolko Systems shared their insights on how Artificial Intelligence and
Machine Learning solutions can address the challenge of healthcare around the
world. These technologies might be a ray of hope that might leave us better
equipped to deal with situations such as these, unlike our predecessors who
lacked the same when they dealt with such a crisis. Health professionals who
have not yet embraced the resources available are likely to understand their
enormous potential and making the improvements and adjustments needed for
simplifying operations, lowering costs, enhancing efficiency and above all
increasing the standard of treatment.

The idea behind this is the need to reduce human interaction,
especially in the current scenario, to diagnose and treat people. This ensures
that doctors are relied upon, only when necessary in times of emergency and
also reduces the risk of contracting the illness due to exposure in a hospital,
hence reducing the spread to a significant extent. Even in the case of
surgeries, robotic aid is often to minimize human error. “We can have
robotic surgeries, where the operator and the team sit outside the OT and
perform the procedure with the help of a console. Thereby again, limiting the
entire team being exposed to the patient on the table” says Prof Rishi
Sethi in #SDGtalks (www.bit.ly/sdgtalks).

Amit Khare, on the other hand, believes that Artificial Intelligence,
along with Machine Learning, can be used to treat issues that are
non-communicable as well. This reasoning is because most treatment is episodic.
He goes on to say, “And because of the episodic treatment, there is no
focus on identifying the non-communicable diseases (NCDs), which are becoming
the leading cause of death (over 70% deaths globally are because of NCDs).
Nevertheless, the doctors to patient ratio is another issue, especially in
India. The WHO recommends a proportion of 900 patients or below for one doctor,
but in India, the proportion is approximately 1700 patients to one doctor.”

And the ratio would not go down anytime soon as a nation cannot
drastically increase (practically double) the number of doctors in a decade.
Many of these diseases require specialists who are even rarer. This problem,
they believe, can only be solved with the help of technology. This made them
come up with this idea which employs data-based decision making and
asynchronous communication to save the vital time of both doctors and patients
by an impressive 30%.

An example of how technology is being used is, suppose a patient comes
with chest pain. The software will ask whether the chest pain is with or
without exertion in an attempt to find more relevant details. So, these
questions decide how the diagnosis and the treatment will proceed. Then the software
would like to know if the pain is radiating or something and suppose the
patient said, “Yes. From the left shoulder.” Since this is very
common in chest pain people, the software will conclude that the left side
implies a heart-related issue. The software tries to find out whether it is
related to the shoulder or it related to chest pain, it could raise your hand,
and that means it’s ruling out the problems with the shoulder. After all, if
the person can raise his/her hand, then it’s good, if it is not, the software
will try to find out whether this is because of the pain, stiffness of the
weakness, or anything else because each symptom has a connotation only a
specialist can understand. These are all very relevant questions. And they
generally go through these. So, once the specialists figure them out, they can
draw accurate conclusions, “The patient is suffering chest pain because of
the shoulder.” The software continues and tries to find out more details
from the patient to see whether it’s like any other non-communicable disease
that can be screened during the interaction with the patient. And that’s a very
precious interaction, as much information should be discovered during this so
that the software can then refer it to the doctor.

The proponents of this technology, i.e., researchers and doctors who
made use of them, reported that the patients informed an astounding 94%
improvement in the quality of care. Amit Khare informed that, “A study
conducted by Harvard University revealed that about 70% of the patients don’t
remember their interaction with the doctor, and this software helps keep track
of it. The patients also felt that they were being heard in more detail, and
they felt more at ease while providing the information. This ultimately helps
in faster and better diagnosis. As of now, about 8 million patients are using
this technology, and they expect this number to increase multi-fold in the
future.”

The technology employs asynchronous communication to save the time of
both doctors and patients. Amit Khare further says that “One of the key
things that technology has done these days and you all would agree, is if we
today, we have to meet like about 100 people, it will be next to impossible.
And, but we can reply to all hundred people using WhatsApp or email which are
the asynchronous means of communication and that we can deal with those 100
messages within an hour or so. So that’s, that’s the advantage of
asynchronously working.”