YOUR EYE ON INNOVATIVE MACHINE LEARNING SOLVING REAL WORLD PROBLEMS
Azafran Capital Partners
INSIGHTS issue FOUR The Healthcare Issue
issue four FOCUS
@ The Intersection of Healthcare + Voice & Acoustics + Machine Learning (ML)
At Azafran Capital Partners, we are focused on investing in end to end solutions solving real world problems derived from a scientific or engineering innovation in machine learning.
The healthcare industry plays a critical role in society for sure, but is also hampered by both inefficiencies and opportunities that are rife for disruption. Issue Four of INSIGHTS focuses a sharp eye on how machine learning, especially driven by voice and acoustics, is and will continue to revolutionize this huge industry and move humanity forward in a positive way. As the chart below highlights, there are a wide range of ways that AI and ML are going to impact healthcare, from the front lines of early detection, to managing and using the incredible mounds of data behind the industry, and enhanced robotics in surgery - which is highlighted as a larger segment opportunity than the other nine categories below. Zeroing in on Azafran Capital’s current focus around voice and acoustics as the growing and primary interface for many of the innovations in healthcare - we are seeing a whole range of companies and technologies both today and on the horizon that will change how we use, administer, apply and think of healthcare going forward. From a high level, some important use cases that we are seeing and looking to invest in the short term, include deep tech looking for vocal patterns such as pitch, tone, rhythm, volume, that serve as powerful data points - "vocal biomarkers." This type of data can help care and clinical teams in their diagnosis of a variety of conditions — from chronic respiratory illnesses to cognitive disorders, early cancer detection (esp. melanoma) and heart attacks. Even simpler areas, such as patient-physician communications, physician’s notes and general patient engagement will be greatly assisted and served by the plethora of ML voice/ acoustic coming onto the market now and the coming months and years.
One of the primary areas of enormous potential we are engaged with is healthcare, the focus of Issue Four of INSIGHTS. Related but through a different lens we look to the area of wellness, which will be the focus of our next issue - our framing and perspective has healthcare as clinical and reactive, wellness more personal and preventative.
The big change in healthcare applications in the future will be the increased use of machine learning techniques. The benefits in, for example, diagnostic applications, are likely to be very significant because machine learning will have a role to play not only in predicting, but also in preventing by early detection, and appropriate treatment by linking known correlations of patient treatment methods. Some medical applications, like the Watson for Oncology system, already uses machine learning, along with other technologies to support cancer detection. The advantages of applications using machine learning technology is their ability to discover new insights from the data, thus moving beyond the traditional limitations of AI. However, the downside of machine learning is that it is predominantly based on black box techniques such as neural networks.” - Keith Darlington on OpenMind
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Volume 1 Issue 4 - Page One