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Healthcare is one of the biggest opportunities for startups and presents some of the greatest frustrations. The market size and its potential to make an impact in people’s lives are nearly unmatched, so are the complications and regulations.

2016 witnessed 73 funding deals in the healthcare sector with investors pouring in $113.45 million in India. These companies promise everything from cancer detection to care and the process of finding a new doctor. Here are the 12 notable ones, combining healthcare and artificial intelligence.

#1. SigTuple

SigTuple uses computer vision and artificial intelligence for diagnosis of various diseases. It uses the same tests and slides for examination and diagnosis as used by pathologists. The process is automated for consistent and faster results.

Firstly, the slides are digitized by attaching mechanical components and a smartphone to a regular microscope. The slides are auto-scanned by a smartphone. Then, the AI engine classifies and tags the visual data. This means, along with telling you that there are 50 eosinophils – it can also show you the same.

Their products Shonit, Shrava, Dhrishti, Aadi, Vaksha and Manthana – in various stages of development.

 #2. Aindra

Dhrishti, a patent pending technology built by the Aindra team is based on artificial intelligence. It provides handheld devices such as smartphone, camera, tablets, and laptops the ability to identify and detect people.

It captures images and sends them to their cloud-based server. Then, the algorithm detects and identifies various objects.

In healthcare, patients use it as an adjunct to their existing patient ids. According to Aindra, you can use this solution to identify your doctors and for doctors to ensure that only intended patients turn up at their referral sites.

 #3. NIRAMAI

NIRAMAI stands for “Non-Invasive Risk Assessment with Machine Intelligence”. Their cancer screening software combines artificial intelligence and thermography images.

Their solution has the ability to detect cancer at much earlier stage than traditional diagnostic methods. Additionally, it is portable, easy to use, and cost effective and demands minimal human supervision.

NIRAMAI’s method of breast cancer screening can identify tumours 5 times smaller than what regular clinical exam can identify. Their non-contact treatment is free of radiation and pain. Their solutions are designed for women to undergo regular breast cancer screening.

Also read: In healthtech, David and Goliath make amends

 #4. OnliDoc

OnliDoc app allows users to find top doctors, book online appointments and helps doctors connect with their follow-up appointments.

The patient can type their symptoms into the app which then uses artificial intelligence to guide the user to the right specialist.

 #5. Ten3T

Ten3T is developing wearable patches (Cicer) for real-time monitoring of cardiac signals and other body vitals.

A 9 cm triangular patch having multiple sensors will continuously collect and stream clinical grade information on ECG, heart rate, respiratory rate, SpO2, and temperature. The patient can place the triangular patch on their chest as long as it requires- from a single minute to several days. Collected data will be transmitted to your cardiologist. Cicer is in beta testing phase, is used by four nursing homes in Bengaluru.

 #6. Qure.ai

Qure.ai uses deep learning technology to diagnose diseases and recommend personalized treatments based on healthcare imaging data. Their algorithms accurately detect and highlight abnormalities – thereby reducing the chances of missing a diagnosis. Further, these algorithms quantify diseases and tumour volumes to monitor the patient’s response to a therapy.

#7. QorQL

QorQL is a doctor appointment booking platform with integrated electronic health record and practice management solution. Their products are:

Qcare – for doctors to manage the health of their patients efficiently.

Qhealth – lets patients monitor their vitals, appointments, electronic health records and reminders. This way the patients can engage with their clinicians, stay connected and self-manage their monitoring.

#8. Touchkin

Touchkin, an “emotionally intelligent” AI platform uses mobile-based social sensing to facilitate proactive personalized care. It enables users to receive personalized behavioral health support from their phone, caregivers, and coaches.

Their two products are:

Wysa – a chatbot to listen and offer evidence based techniques to improve your mood.

StayClose – it analyses the way you use your phone to analyze your mood.

#9. Predible Health

Predible health offers quantitative reporting for surgical planning powered by Automated Liver Segmentation.

They deliver radiology reporting by combining the power of cloud computing and deep learning. Their algorithm automatically learns from the past medical records and provides physicians with the most relevant clinical insights.

Also read: Data, analytics, and using simple solutions to create a huge impact, a discussion on healthcare innovation at Echelon Asia Summit 2017

Additionally, it provides advanced analysis of multiphase CT scans.

#10. Healthmir

Healthmir, a health engagement platform educates the consumer about the importance of diagnosis and guides pre and post health treatment through artificial intelligence tools using video demos.

#11. Tricog Health Services

The Tricog platform helps healthcare centers to install a cloud-based ECG machine. When the doctor takes the patient’s ECG, the information is transmitted to their central hub where a qualified doctor is available 24/7. This specialist interprets the ECG and sends a report both as an SMS and as a message on the Tricog app. This increases the speed of diagnosis. The Tricog technology is designed for early detection, to take quicker action and for constant monitoring of the patient’s health.

#12. Advenio Tecnosys

The two clinical imaging tools developed by Advenio Technosys are:

  • iCheck: CADx for ophthalmology has the ability to detect retinal abnormalities for fundus images.
  • Ri-view: CADx for radiology deals with the diagnosis TB using the chest X-Ray.

They use artificial intelligence, deep learning and machine learning based computer assisted detection for these processes.

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