ML in Digital Pathology & Customized Solutions || Nucleai Medical|RSIP Vision

We will have two lectures (approx. 35-40 minutes each) in Hebrew. Light refreshments will be served before the first lecture.

Estimated schedule:
1800 refreshments at our conference hall (1st floor)
1830 First lecture
1920 Second lecture

First lecture:

Lecturer:
Ran Shadmi
Senior Machine Learning, Deep Learning & Computer Vision Algorithms Developer
Nucleai Medical

Title:
Applying AI on digital pathology, challenges & success stories

Abstract:
Pathology is a branch of the medical science that involves the study and diagnosis of disease through the examination of surgically removed tissues. Digital pathology and more specifically Whole-Slide Imaging (WSI) converts entire glass slides into a digital format that can be viewed, managed and analyzed on a computer screen. The field of digital pathology is currently regarded as one of the most promising avenues of diagnostic medicine in order to achieve better diagnosis of cancer and other important diseases. Many technical challenges arise when trying to apply current state-of-the-arts algorithms to digital slides; each slide contains many billions of pixels and represent a highly complex anatomical data. Very few public data-sets exist and storing, accessing and annotating slides proves to be major technical difficulty by itself.
I'm going a give a talk describing the challenges and some of our success stories for applying deep-learning / machine-learning / computer-vision algorithms on digital pathology slides. I'll review some of the work done in Nucleai and share some insights, both unique to the filed of digital pathology and some common to many other medical applications.

Bio:
Ran Shadmi is an algorithm developer and software engineer for image processing, computer vision, machine learning and deep learning applications. Ran holds a a biomedical engineering master's degree from Tel Aviv University, specializing in medical image processing. In recent years Ran has focused on applying his technical skills to the development of medical applications. In Zebra Medical, Ran developed the Coronary Calcium Scoring algorithm (FDA approved) as well as automatic detection of abnormalities in chest X-ray images. Ran joined Nucleai in early 2018 as its first employee and initiated the development of the company’s algorithmic infrastructure.

Second lecture:

Lecturer:
Miki Haimovich
VP Business Development
RSIP Vision

Title:
Customized AI solutions for medical applications

Abstract:
Firstly we will review various aspects of ML solutions in the medical field, the trade off between them, as well as the variety of optimization points enabled by customized solutions, then we will review several examples of customized AI solutions developed by RSIP Vision along the years.

Bio:
Miki Haimovich is VP Business Development with RSIP Vision. As such he spends most of his time communicating with customers and prospects, to understand their needs and present RSIP Vision Solutions to these needs. Miki finds the ongoing discussions between customers in the medical field, and computer scientists developing AI solutions for them, to be not only crucial but also fascinating.