Philips Innovation Centre is taking India, and startups’, AI products to the globe


Philips intends to help startups in the healthcare sector to go global and believes a truly democratic healthcare system involves the work of government, startups and privately-held companies.

Walk into the Philips Innovation Centre campus in Bengaluru and ideas like Machine Learning and Artificial Intelligence suddenly take on a tangible form.

With over 2,500 people at the campus, including engineers, doctors, researchers, data scientists and software developers, the R&D center hosts all Philips businesses: Imaging systems - CT, MR, ultrasound, interventional X Ray, diagnostic X Ray; healthcare informatics, hospital to home care, critical care, clinical applications and healthcare transformation services.

The center is home to Philips’ research, design and intellectual property and standards team. Globally Royal Philips' total intellectual property portfolio consists of 62,000 patent rights, 37,600 trademarks, 47,800 design rights and 3,000 domain names.

The company filed 1,200 new patents in 2017, and put in strong focus on the areas of health and well-being. Its CEO M R Srinivasaprasad is a man who believes cognitive intelligence can democratise healthcare in India.

He also believes India cannot democratise care if each party tries to achieve outcomes by themselves, and calls for partnerships with government, startups, hospitals and private companies such as Philips to achieve outcomes.

He tells YourStory the challenge is to integrate patient data, devices and personal health data, which is vast and an ambitious undertaking—a challenge garnering much attention of late with the promises of cognitive computing, the Internet of Things, big data analytics, wireless wearable technology, and cloud platforms.

Below are edited excerpts of the interview.

M R Srinivasaprasad, CEO of Philips Innovation Centre

YourStory: What work have you done with startups and what advice do you give them?

M R Srinivasaprasad: We have a global entrepreneur programme called healthworks. However, I have one advice for startups in India, which is they don’t have to build everything from scratch. They should focus on software and data skills. They should work with us, as we at Philips have access to so much clinical data globally.

I see startups go to individual hospitals and they get monthly projects. They are not able to scale up after a pilot project. Philips HealthWorks invests in, partners with, and empowers entrepreneurs to turn great ideas into innovations that can transform personal health and professional healthcare worldwide.

The programme provides access to a network of experts, investors and healthcare partners. We have created global innovation hubs and a healthcare-compliant technology platform that will help entrepreneurs de-risk and accelerate time-to-revenue.

The programme is an intensive 12-weeks designed to help start-ups build, test, de-risk and scale their ideas. We have had four startups from Bengaluru - Niramai, Parentlane, Theranosis, and Touchkin - participate in the programme. For me, the combination of cognitive intelligence expertise, provided jointly by startups and Philips, becomes a very powerful platform. Our second cohort of startups will be called for soon, and we are looking at ideas across healthcare verticals. Like I said, startups must remember to focus on core technology instead of focusing on data gathering.

YS: What innovations can we expect to scale up from PIC?

MRS: In India, Philips recently launched Healthcare@Home, providing home healthcare treatment, diagnosis and care in the areas of critical care, respiratory disease, wound management, post-surgical rehabilitation and sleep disorders.

The services are provided through a Philips team of nurses, respiratory therapists, and other trained personnel, who will be monitored remotely by doctors, and a technology and analytics backend. This is completely driven by modern day mobile solutions.

The solution integrates data from disparate connected devices into a secure repository, and builds a complete picture of a patient's health without compromising privacy. The solution extends the care coordination platform (eCare Coordinator) to support clinical protocols and workflows that are required in India.

It then connects this data with the right clinical expertise. Physicians access a patient's data and intervene, if necessary, through a mobile application.

We also focus on disease specifics. For example, tuberculosis (TB) has been a major global health challenge, especially in developing countries. Despite the availability of excellent treatment options, the mortality rate in many countries is high due to delayed diagnosis and availability of qualified radiologists. There is a need for an automatic screening solution based on Deep Learning algorithms with high specificity (to capture almost all TB cases) rather than sensitivity (low false positives). Chest X-ray is typically used for screening TB.

Philips has developed an AI-based solution to detect TB which helps reduce the workload on radiologists and makes their work less subjective. Given a set of chest x-rays, the algorithm is able to detect if there are traces of TB in the image.

The solution learns TB-specific features from the images which are unique in chest X-rays using deep learning techniques and then use machine learning algorithms to generate models that can distinguish a chest X-ray that contains TB traces from the normal ones.

YS: So, radiologists would love to use AI in the future?

MRS: This is already happening in India. The ML model can detect lesions in an MRI brain study, and also segment various parts of a tumour, like necrosis, edema, enhancing edema. One of the benefits of having such a model is to improve the productivity of a radiologist – since it takes considerable time, which is between 20 to 30 minutes to go through multiple slices present in different sequences, and identify the lesions present in different slices.

The same task can automatically be done through the model, thus saving time for a radiologist. As soon as the scanner scans the MRI of a patient and pushes the study to the workstation, this model can be executed in the background and segmented so that when the radiologist opens the study, the lesion is already segmented.

YS: You are very passionate about India and what it can achieve in healthcare.

MRS: We all know that in India, we have extremes. Healthcare is something where India should learn to lead. We have global solutions and the talent to do so. The good thing is that in this budget, the government has given focus to healthcare, and sanctioned Rs 1,500 crore to transform primary care.

It also announced a large insurance programme. Without the joint effort of all stakeholders India, it will never be able to make healthcare universal. Today there is technology that can democratise care, we only need to ensure that reaches the people.


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