We explore what the algorithm behind voice and image recognition can do for drug discovery. We apply sophisticated algorithms to analyse and mine different data sources to predict molecular behavior and suitability as lead compounds.
CNNs share the common features of all deep learning algorithms: stacked layers of neuronal subunits that learn hierarchical representations (allowing the data to be understood at various levels of abstraction, in isolation or combination), the ability to perform unsupervised pre-training on unlabeled data and efficient parallelization on multiple core GPUs which can result in improvements of up to 5000% over CPU-only implementations.
What happens when the diagnostics is automated? The E-Doctor will see you now! Vingyani is looking for partners and investors to develop the E-Doctor. Vingyani also would like to explore the possibility to work with the start ups who are already working on this project. As we are a deep learning CRO, we can partner with you to develop your project. As AI evolves, the doctor’s role will inevitably be reimagined as computers make more decisions and patients gain more power. Data won’t just be shared with doctors, but with patients as well, fueling a movement in which patients are better-informed and unrestrained by geography.