How AI Assists Doctors in Inpatient Practice

How AI Assists Doctors in Inpatient Practice

We have previously discussed how artificial intelligence (AI) allows to improve the quality of outpatient healthcare. Let’s talk more about AI development in the healthcare sector.

We have previously discussed how artificial intelligence (AI) allows to improve the quality of outpatient healthcare. Let’s talk more about AI development in the healthcare sector.

Nowadays, heads of healthcare institutions and venture investors heavily invest in the development of medical AI technology. Some of the leading medical institutions in the US (Mayo Clinic, Cleveland Clinic, Massachusetts General Hospital, Johns Hopkins Hospital, and UCLA Medical Center) have already introduced and are successfully using AI-based applications in inpatient practice, improving diagnosis process and increasing care quality.

AI in the ER and ICU

Image for post

Patients in severe life-threatening conditions are admitted to the emergency rooms (ER) and intensive care units (ICU). A great number of various indicators, such as blood pressure, heart rate, blood oxygen saturation (SpO2), liver and kidney function indices and many others, are used to monitor such patients and decide on the required treatment. It is important to process and interpret these data accurately and promptly as the patient’s life depends on it. AI assists MDs in predicting risks of life-threatening conditions and alarms medical staff when an urgent attention is needed.

In 2016, the University of San Francisco has developed and tested an AI-based app designed to detect sepsis (a life-threatening condition that occurs when an infection enters the blood). Using various data (blood pressure, heart rate, body temperature, respiratory rate, SpO2, WBC count, patient’s age and others), AI predicts the risk of sepsis occurrence, alarming medical staff if needed. This tool allowed to reduce the mortality rate in the hospital by ≥12%. Duke University and the Johns Hopkins Hospital use similar AI algorithms for early detection of sepsis.

machine-learning inpatient-treatment data-science data analysis

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

15 Machine Learning and Data Science Project Ideas with Datasets

Learning is a new fun in the field of Machine Learning and Data Science. In this article, we’ll be discussing 15 machine learning and data science projects.

Applied Data Analysis in Python Machine Learning and Data Science | Scikit-Learn

Applied Data Analysis in Python Machine learning and Data science, we will investigate the use of scikit-learn for machine learning to discover things about whatever data may come across your desk.

Most popular Data Science and Machine Learning courses — July 2020

Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant

Exploratory Data Analysis is a significant part of Data Science

You will discover Exploratory Data Analysis (EDA), the techniques and tactics that you can use, and why you should be performing EDA on your next problem.

Why You Should Learn R — Learn Data Science with Dataquest

Why should you learn R programming when you're aiming to learn data science? Here are six reasons why R is the right language for you.