Radical Reads: Diagnosing the Mind

Sanjana Basu


Fever, trouble swallowing, sore throat: these are the tell-tale symptoms of strep throat. But before a doctor decides to prescribe an antibiotic, she may first conduct a throat swab to confirm the presence of streptococcus bacteria. Such reliable tools are the cornerstone of modern medicine — think of biopsies, glucose monitors, MRIs and x-rays. But, when it comes to mental health, definitive diagnostic technologies remain elusive.

Last week Amber, a Google X project, publicized efforts to use artificial intelligence (AI) to identify biomarkers for depression. The project aims to provide an accurate and objective measure of mental health, which could solve a significant challenge in behavioural care.

From diagnosis to treatment, we believe AI will play a major role in nearly every aspect of healthcare, including behavioural health (see Radical’s framework on the two waves of digital health innovation published earlier this year). According to CB insights’ Q3 2020 State of Healthcare report, total VC investment in the mental health space reached close to $1.5B in 2020.

Aside from leveraging AI to develop new ways to discover biomarkers and diagnose concerns, AI will also help determine treatment pathways that could include prescription digital therapeutics and computerized cognitive behavioural therapy. Covid-19 has only intensified demand for mental health services and AI can play a critical role in mitigating the impact of what some experts worry could be the next pandemic.


5 Noteworthy AI and Deep Tech Articles: week of Nov 16, 2020 

1. Radical Scale: Secrets of Customer Success (Radical Ventures)
Radical Scale is a regular feature exploring key strategies for growing early stage technology companies. This issue of Radical Scale looks at best practices for scaling customer success with Paul Teshima, Chief Client Experience Officer at Wealthsimple.

2.  AI has cracked a key mathematical puzzle for understanding our world (MIT Technology Review)
Partial differential equations (PDEs) are a category of math equations that use highly complex calculations to illustrate change over space and time. Researchers have introduced a new deep learning technique for solving PDEs that would help scientific inquiry, engineering and a better understanding of our physical universe.

3. What a Biden-Harris administration means for artificial intelligence (Fortune)
The Biden administration has not detailed exact plans for AI research, but the Democrat’s campaign indicated that it considers general scientific research and development to be crucial to the nation. President-elect Biden has proposed to increase the amount of federal R&D spending to $300B over four years.

4. Scientists use artificial intelligence to forecast large-scale traffic patterns more accurately (Tech Xplore)
Scientists are using machine learning to look at traffic patterns from a year’s worth of data taken from over 11,000 sensors along LA’s highway system. That information was then used to train a model to forecast traffic at lightning fast speeds. Within milliseconds, the model can look at the past hour of data and accurately predict the next hour of traffic.

5. This could lead to the next big breakthrough in common sense AI (MIT Technology Review)
New research is exploring how models that incorporate both language and visual inputs may help AI systems better navigate and “see”. The research applies some of the same methodologies that have made traditional natural language processing architectures successful to image data, deepening a computer’s capacity to understand and communicate the visual world.


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