BrainScanology: Inventing Algorithms for Detecting Diseases
David is a serial entrepreneur. He is the co-founder and CEO of BrainScanology, a platform that creates the best shape analysis software in the world to analyze organs and cells from MRI/CT/X-ray/ultrasound and microscopy images. In an interview, he speaks on an array of topics.
Conception of BrainScanology
The current assessment of disease states based on images from MRI/CT/X-ray/ultrasound is highly subjective, says David. “This leads to long diagnostic wait times, misdiagnosis, and underdiagnosis. Traditional measures of length, area, and volume have reached an accuracy plateau, because Machine Learning models based on them have problems generalizing – meaning work well – on new data sets. There needed a more powerful way of measuring the complex shapes of organs that allows for rapid and objective diagnostic models to aid in clinical decision making.” His college roommate and friend suffered from bipolar disorder and took his own life years after college. Then his favorite high school biology teacher died of an aggressive form of colon cancer. These two losses would plant the seed for the algorithms that created BrainScanology.
Patient Healthcare-challenges Galore
The COVID-19 pandemic has made clear that we need more remote diagnostic tools that minimize in-person visits, especially for chronic health problems that require recurring visits. A major problem with diagnostic methods based on Artificial Intelligence and Machine Learning is data bias regarding race and sex. “Once size does not fit all, so the technology must be trained on medical data from diverse pools of data that incorporate racial and sex differences. Otherwise, females and minority groups receive misdiagnosis and under-diagnosis, which increases suffering and mortality.”
Benefits of BrainScanology’s Solution
“Our method is 1,000X more sensitive at measuring differences in shape compared to area and volume. This means that compared to existing methods, it is much more likely to discover new subtypes of disease based on existing imaging data. It is in a better position to create predictive models that are faster, and thus less expensive, than methods that require analyzing the full 3D shape of an organ.” Furthermore, the platform also measures shape and not signal intensity. The technology works also on low-resolution images, such as from ultrasound and older MRI machines.
“My personal philosophy is that growth requires discomfort while motivation requires vision. Everyone on the team plays an important role, no matter their ranking. Even though standards need to be high, people need room learn, stumble, and blossom into their future glory.” David moots for sympathy and empathy as core traits of a team leader. Without these, resilience, vision, and talent cannot build teams. Leaders work hard to pave the way, making things better for their team. This requires sacrifice, leading by example, integrity, and consistency, he adds.
David also suggests leaders make honest conversations which in turn would reveal that everyone makes mistakes. “The important thing is learning how to overcome those inevitable mistakes.”
The Success Mantra
David maintains that it is important to develop a great personal and professional network and expect that at least 50% of the experts you talk to won’t think that your goal will succeed. “For those who have the courage to be pioneers, many experts must believe that you will fail. Otherwise, are you really a pioneer? Also, it confirms that your goal is worthy of your effort. Trailblazing, inside or outside the context of entrepreneurship, means many experts must be wrong because your vision actualizes what theirs cannot.”
While ShapeGenie, our shape-analysis SaaS software, will be a stand-alone product, BrainScanology can guide you on the nuances on what parameters to control for to maximize the differences in your data. “Unlike the area and volume of an object, which don’t change based on how you rotate the object, the way we measure shape is so sensitive that you need a systematic reason about why you orient an object before measuring its shape. Trust me, I invented this algorithm.”