We propose a scalable and data-driven approach to learn shape distributions from large databases of healthy organs. To do so, volumetric segmentation masks are embedded into common probabilistic space that is learned with variational auto-encoding network. The resulting latent representations leveraged derive zeroshot few-shot methods for abnormal detection. proposed distribution learning illus...

In this paper the author presents a kind of Soft Computing Technique, mainly an application of fuzzy set theory of Prof. Zadeh [16], on a problem of Medical Experts Systems. The choosen problem is on design of a physician’s decision model which can take crisp as well as fuzzy data as input, unlike the traditional models. The author presents a mathematical model based on fuzzy set theory for phy...

AI techniques, massive parallel computing, and specialized processors have evolved to the point where AI usage is now practical and beneficial for a wide variety of applications. As its capabilities continue to expand, widespread usage in the near future is inevitable. AI has the potential to significantly increase the quality of health care while decreasing overall costs. Advanced diagnostic a...