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Vision4Doctor

MedTech DeepTech

System for recognition and processing of surgical operations based on artificial intelligence.

Preparation of robotic automatic surgery.

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Problems

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After the operation, the tired surgeon has to fill out the protocol of the operation with a description of what was done.

According to statistics, about 3,000 items forgotten in patients are found annually in Russia.

In case of an unsuccessful operation, insurance companies and investigators are forced to analyze the past operation without having all the data.

It is impossible to understand the doctor's deviation from the "ideal technological map", no records of errors are kept. Successful or unsuccessful experience of the doctor remains only with him. Important reactions to non-standard situations are lost.

It is impossible to streamly control the quality and professionalism of a doctor.

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Solutions

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The system sees, analyzes and recognizes everything that happens in the operating room. The protocol of the operation is formed during the operation and is ready immediately after its completion.

The system knows the number of tools and material "at the input" and will report if there is a discrepancy "at the output".

Insurance companies and investigators see the full picture of the past operation.

The system sees, recognizes, analyzes and clearly records all intraoperative events, collects the experience of doctors and forms a database for AI training.

The actions of doctors can be analyzed, work with errors, teach young students and interns.

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Collection and synchronization of data from the operating room

Overview

camera

Head camera

surgeon 2

Head camera

surgeon 1

Endoscope

Instrumental

table

Monitor

patient

Surgical

microscope

Camera in

operating room lamp

4

Laparoscopy

Ultrasound

Angiograph

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Formation of a multimedia library

5

Recording

video

Synchronization

video

Treatment

video

Recognition

video

Markup

video on

stages and events

Definition of intraoperative events

Determination of the surgeon's actions

Definition of pathologies

Recording

video

Synchronization

video

Treatment

video

Recognition

video

Markup

video on

stages and events

Manual

process

Auto

process

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Data shaping

for AI

We are building a database for training artificial intelligence.

In the next 10 years, we expect to replace doctors with robots, and the data obtained today will form the basis of first robotic semi-automated, and later robotic automatic surgery.

Outlying territories, Mars, will receive high-quality surgery. The success of the operation will no longer depend on the professionalism of the surgeon.

We have already started preparing.

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Look beyond the horizon

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2008�2007

Smartphone

2012�2004

Social media

2019�2009

Taxi

2023�2015

Ai

?�2025

Robotic automated surgery

Predict and change the future

Accept the existing habitual

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Subsequence

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Selling data to surgical robot developers

Operating room equipment

Recording of operations

Synchronization and markup

Storage

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The First Evangelists

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Fomin Clinics

23 clinics

https://fomin-clinic.ru/

SM-Clinic

15 clinics

https://www.smclinic.ru/

Moscow Regional Research Clinical Institute named after M.F. Vladimirsky (State Budgetary Healthcare Institution of the Moscow Region MONIKI named after M.F. Vladimirsky) + Clinics of the Moscow Region

34 clinics

https://www.monikiweb.ru/

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RoadMap -

for first year

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Functional

Benefits for clinics

Platform for storing and annotating video operations

1. Secure storage for endoscopic surgery videos (with data security standards)

2. Simple annotation tools for doctors: marking key stages of surgery, adding comments

3. Possibility of sharing for training and analysis of complex cases

4. Formation of a directory of selected entities, such as instruments, organs, colors, textures, etc.

1. Centralized location for data storage

2. Simplify internal training and analysis

Error Analysis and Recommendations Tool

1. Automatic video analysis to identify key moments of the operation (e.g. start, end, critical stages)

2. Simple report with statistics (e.g. duration of operation stages)

1. Possibility of quick analysis of standard procedures

2. Reduction of the number of errors

Automatic video tagging of key stages

1. A simple algorithm that automatically marks the stages of an operation (e.g., cutting, working with instruments, finishing)

2. Generating a report on the stages and the time it took to complete them

1. Saving time on manual video analysis

2. Basic analysis of the efficiency of operations

System for improving the quality of medical protocols

1. Identification of discrepancies in the surgeon's actions with standard protocols

2. Automatic creation of individual recommendations based on the collected data.

1. Simplifying the transition to standards

2. Improving the quality of treatment

Estimated implementation time

2-3 months: Video storage with annotations

6-9 months: Automatic analysis of errors or stages (here the MVP is finished and there are sales)

6-12 months: A tool associated with high-quality recommendations.

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Media

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Scientists have taught a robot to stitch patients by showing it videos of surgeries.

2020

Stitching a patient up after surgery is an important but monotonous task for doctors, often requiring them to repeat the same simple movements over and over hundreds of times. But thanks to a joint effort between Intel and the University of California, Berkeley, surgeons of the future could hand off the heavy lifting to robots — like a macro, but for automated stitching.

https://www.engadget.com/intel-uc-berkeley-motion2vec-ai-robot-surgery-203003829.html

Controlled Autonomous Robotic Soft Tissue Surgery

2016

The operating room may one day be run by robots, with surgeons controlling their actions. Shademan et al. developed the “Smart Tissue Autonomous Robot,” or STAR, which includes suture instruments, as well as fluorescence and 3D imaging, force measurement, and submillimeter positioning. With all these components, the authors were able to use STAR for soft tissue surgery, a challenging task for a robot given the deformation and mobility of tissue. Surgeons tested STAR against manual surgery, laparoscopy, and robotic surgery for intestinal anastomosis in pigs, and found that the controlled autonomous surgery offered by the STAR system was superior.

https://www.science.org/doi/10.1126/scitranslmed.aad9398#con1

This AI Learned to Perform Surgeries by Watching Videos, and Now It's Ready to Operate on Humans

2024

A new smart robot developed by researchers at Johns Hopkins University and Stanford University learned by watching videos of surgeries. It can now perform procedures with the skill level of a human doctor.

https://www.fastcompany.com/91226566/doctors-built-an-ai-that-taught-itself-how-to-do-surgery-and-its-ready-to-work-on-humans

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Team

Vadim Potekhin

CEO, founder

Visionary serial tech entrepreneur with expertise in digital transformation across Proptech, Fintech and Medtech.

Linkedin Telegram

9241115@gmail.com

+79859241115

Alexander Terentyev

CTO, co-founder

Experienced CTO and development team lead with more than 10 years of experience in complex IT ML

projects.

Linkedin

Leonid Belskikh

Curator, co-founder

Head of the Surgical Center for the Coordination of Organ Donation and Transplantology, GBUZ MO MONIKI named after A.I. M.F. Vladimirsky.

Linkedin

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