Artificial intelligence in mental health

How artificial intelligence eases pressing needs of mental health

Artificial Intelligence and machine learning are making significant inroads with respect to mental healthcare systems. These emerging technologies allow the mapping of the brain’s responses to various stimuli and help in predicting disorders.

The discussion around innovation in healthcare has progressed rapidly. One strong ally is deep tech. Artificial intelligence helps accelerate the modernization of healthcare. Mental health, especially, is one such area that needs the speed of computational power, processing of vast amount of data and quicker turnaround time.

Madhurima Agarwal, Director, NetApp and Ravi Chabbria, MD, NetApp in an interview with Dataquest throw light on the advent of AI in modern healthcare data management, the use cases derived and how the technology helps ease the pressing needs of mental health.

Edited excerpts:

How will AI be used in the modern healthcare data management. What are the use cases derived out of it?

The healthcare segment has seen massive transformation due to analytics and data, right from maintaining electronic health records to deriving insights for mental health analyses. According to IDC, healthcare organizations in India are on the path to accelerate their adoption of AI solutions due to the pandemic. Facets of healthcare data management that are to be redefined by AI include: leveraging the power of quality patient data for a clinical decision support system, increased priority on electronic medical records, early predictability of cancer and heart attacks and AI based imaging solutions.

[Also Read: Using artificial intelligence for greater good]

The pandemic has especially caused a positive inclination in the adoption of AI and data management for healthcare. Our work with AstraZeneca reflects the need for a unified data infrastructure that can handle complex data. AstraZeneca is using our solutions to scale with all the three major public cloud providers and build a hybrid, multi-cloud data fabric to move data across cloud – be it is private, public or hybrid. With this, AstraZeneca could speed up the discovery process for life-saving treatments, largely because dispersed researchers could access the data they needed, real-time.

We are also witnessing an upward trend across startups and VCs focusing on transforming the healthcare sector.

How the pressing needs of mental health can be eased with AI and ML?

Artificial Intelligence and machine learning are making significant inroads with respect to mental healthcare systems. These emerging technologies allow the mapping of the brain’s responses to various stimuli and help in predicting disorders. The vast amount of data created is impossible to be computed by humans and hence technologies like AI and ML are needed to derive insights from these data points. Utilizing high computational speed with smart device capability, and other enabling technologies, the monitoring of a person’s mental state is now a field of digital medicine that is rapidly progressing.

[Also Read: 4 books on Machine Learning that you cannot miss in 2021]

BrainSightAI, from cohort 7, is pioneering this field of medicine. Their mobile app uses an unsupervised learning model to track the user’s sleeping patterns. This helps streamline patient history through a smart combination of symptom tracker, phone sensors, and artificial intelligence and acts as a complimentary data source for doctors and therapists. Similarly, they also provide a platform that makes functional MRI analysis readily accessible to clinical practitioners for investigating disorders, treatment approaches and surgical planning with an AI powered engine. This helps drastically reduce turnaround time and provides reports with rich insights.

How emerging areas of healthcare, industrial IoT and customer experience are being redefined during the pandemic?

The startups of NetApp Excellerator cohort 7 are transforming the emerging areas of healthcare, industrial IoT and customer experience with industry relevant technologies.

In the healthcare space, Arintra is working on developing AI-enabled platform for reducing clinical overload on doctors while BrainSightAI is pioneering new tools for understanding the human brain to aid mental health diagnoses. As mentioned above, health tech startups are seeing a massive spurt in demand post the pandemic and these startups are already disrupting the landscape.

[Also Read: Why growth of deep tech startups is key for India]

Litmus Automation is one of our startups that is revolutionizing the space of industrial IoT. The need for a connected and intelligent world is apparent, now more than ever. Litmus provides the critical asset connectivity, data intelligence and application enablement needed to usher in industry 4.0.

Blinkin, has done some cutting-edge work during the pandemic. Their technology combines deep learning, big data, and proprietary computer vision algorithms to provide customers and support representatives with intelligent visual assistance. Their biggest use case was to help German manufacturers install ventilators in Wuhan medical centres remotely, using augmented reality.

 

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