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Artificial Intelligence, Machine Learning, Startup India Strategist, Startup Lawyer India

Deploy Artificial Intelligence & Machine learning

Deploy Artificial Intelligence & Machine learning in Medical Diagnosis

India is experiencing 22-25 % growth in medical tourism and the industry is expected to double its size from present (April 2017) US$ 3 billion to US$ 6 billion by 2018. Medical tourist arrivals in India increased more than 50 per cent to 200,000 in 2016 from 130,000 in 2015. Affordable medicines and good doctors is very lucrative to patients across the globe. Medical tourism is on rise and Indian healthcare industry operates in both private and public sectors.

Healthcare industry in India has come a long way in terms of advancement. The ultimate AIM of research and development in medical diagnostics is to be able to identify different diseases and diagnose them correctly.

Current Drawbacks

Despite ever-improving diagnostic technology, crucial time and valuable resources are lost everyday due to “Misdiagnosis” resulting in unnecessary tests, delayed treatment and present a threat to the health and life of the patients.

Artificial Intelligence and Machine learning are NEW AGE Technologies

 Machine Learning (ML) and Artificial Intelligence (AI) are transformative technologies in most areas of our lives.

Artificial Intelligence and Machine learning offers tremendous opportunities for the healthcare industry. The use of machine learning in identifying and diagnosing, diseases has actually been one of the biggest breakthroughs in the medical industry.

Intelligence is the ability to learn or the ability to think and reason and Artificial intelligence refers to programming computers and machines to exhibit seemingly intelligent behaviour based on software algorithms.

Today Machines are capable of analysing and interpreting medical scans with super-human performance are within reach. Deep learning, in particular, has emerged as a promising tool and is able to detect brain damage automatically.

WHAT is the Challenge?

How do we know when the machine gets it wrong?

Can we predict failure, and can we make the machine robust to changes in the clinical data?

Human brain is the greatest gift of god. NO machine and neural network can mimic the spiking of neurons just like human brain. The CURIOSITY of human mind to answer questions of HOW, WHAT, WHY and WHEN which is able to take the human mind to even radiate electromagnetic signals differentiates us from machines.

Computers can analyse massive amounts of data at a rapid speed and with higher accuracy as compared to humans. With the help of Computers and the algorithms they run scientists, physicians and medical practitioners or professionals can get better insight into patient’s health and condition and thus can make better decisions regarding the treatment.

Healthcare has become a key industry for investment in the field of Artificial Intelligence and Machine Learning based on its potential to improve health care system and save lives and money.

Some healthcare and technology innovators are collaborating and trying to change our current reality by experimenting with artificial intelligence (AI) and machine learning. Not only have major players such as IBM and Microsoft jumped into their own AI healthcare projects, but several start-ups and smaller organizations have begun their own efforts to create tools to aid healthcare.

And, the savings would be tremendous. One report from McKinsey estimates big data could save medicine and pharma up to $100B annually as a result of improved efficiencies in clinical trials and research, better insight for decision-making and new tools that will help insurers, regulators, physicians and consumers make better decisions.

Machine learning algorithms improve the more data they are exposed to.

If there is one thing the healthcare systems has in abundance, it’s data. Due to different storage systems, ownership and privacy concerns, and no established process that allows people to easily share data with each other, there is a major amount of analysis that’s not currently being done that could glean tremendous results for patients, doctors and healthcare organizations.

Artificial Intelligence (AI) aids in disease identification and diagnosis Much of the AI work done thus far in healthcare is focused on disease identification and diagnosis. From Sophia Genetics that is using AI to evaluate DNA to diagnose illnesses to smartphone apps that can determine a concussion and monitor other concerns such as newborn jaundice, lung function of those suffering from chronic respiratory diseases, blood pressure, hemoglobin levels and even evaluate coughs, disease and health monitoring is at the forefront of the machine learning efforts. Since heart disease is a primary killer of human beings around the world, it’s no surprise that effort and focus from many AI innovators is on heart disease diagnosis and prevention.

The current process to determine an individual’s risk factor for a heart attack is to look at the American College of Cardiology/American Heart Association’s (ACC/AHA) list of risk factors that include age, blood pressure and more. However, this is really a simplistic approach and doesn’t take into account medications someone might be on, the health of the patient’s other biological systems and other factors that could increase odds of a heart ailment. Several research teams, including those at Carnegie Mellon University and a study from Stephen Weng and his associates at University of Nottingham in the United Kingdom, are working toward enhancing machine learning so algorithms will be able to predict (better than humans) who is at risk and when they might be at risk for a heart attack. Preliminary results of the AI algorithms were significantly better at predicting heart attacks than the ACC/AHA guidelines. From liver disease to cancer and even psychosis and Schizophrenia, AI algorithms are changing the game in terms of disease diagnosis. Machines are now learning how to read CT scans and other imaging diagnostic tests to identify abnormalities. Although some predict the end of radiologists as we know them, others see AI acting as a radiologist’s assistant.

How Can we at TCIS, INDIA assist YOU with YOUR Artificial Intelligence & Machine learning Research?

Analysis of medical technologies is essential to development in modern medicine. With the increasing amount of patient data also known as BIG DATA, new challenges and opportunities arise for different phases of the clinical routine, such as diagnosis, treatment and monitoring.

WE at TCIS, INDIA focus on the patent and non-patent literature (NPL) analysis of technologies related to Artificial Intelligence & Machine learning Research. We use state of the art patent research techniques which is very helpful to scientists across the globe.

Technologies we have worked on in recent past:

  • Automatic delineation and measurement techniques
  • Monitoring disease progression
  • Computer-aided diagnosis,
  • Personalized medicine and
  • Efficient data management and big data analysis

Our mission at TCIS, INDIA is to advance the state of the prior art studies and freedom to operate analysis. I have personally researched more than 1000++ technologies over a span of 12++ years. Our team of patent geeks are enthusiastic about performing patent research.

Success Stories

George Yu Partner at Schiff Hardin LLP

April 26, 2017, George was a client of Prity Khastgir IPR’S

Prity is very knowledgeable and experience when it comes to IP support functions.

SULABH MANGAL

Director at Energia International

July 19, 2017, Sulabh was a client of Prity Khastgir

‘Ridiculously efficient’ is the phrase that comes to mind when I think about Prity Khastgir. It’s rare that you come across standout talent like her. We hired her for patent filing and her execution is flawless.

PRASAD SHETTY

Co-Founder & Managing Partner Stryde Medical

May 20, 2017, Prasad was a client of Prity Khastgir IPR’S

Prity is a complete rebel. A hard task master and wastes know time in getting to the point! With such a vast experience, Prity definitely has the edge.More importantly she has come across to me as extremely smart, witty and a go-getter! I wish her all the luck for her future endeavours.

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