Tag Archives: healthcare
Lung Disease Prediction using Machine Learning
Lung diseases, including chronic obstructive pulmonary disease (COPD), are a leading cause of death worldwide. Early detection and treatment are critical for improving patient outcomes, but diagnosing lung diseases can be challenging. Machine learning (ML) models are transforming the field of pulmonology by enabling faster and more accurate prediction of lung diseases including COPD. In this blog, we’ll discuss the challenges of detecting / predicting lung diseases using machine learning, the clinical dataset used in research, supervised learning method used for building machine learning models. Challenges in Detecting Lung Diseases with Machine Learning Detecting and predicting lung diseases using machine learning can be challenging due to a lack of labeled …
Machine Learning: Identify New Features for Disease Diagnosis
When diagnosing diseases that require X-rays and image-based scans, such as cancer, one of the most important steps is analyzing the images to determine the disease stage and to characterize the affected area. This information is central to understanding clinical prognosis and for determining the most appropriate treatment. Developing machine learning (ML) / deep learning (DL) based solutions to assist with the image analysis represents a compelling research area with many potential applications. Traditional modeling techniques have shown that deep learning models can accurately identify and classify diseases in X-rays and image-based scans and can even predict patient prognosis using known features, such as the size or shape of the …
Diabetes Detection & Machine Learning / AI
Diabetes is a chronic disease that affects millions of people worldwide. The early detection of diabetes is crucial to preventing the development of serious complications. However, traditional methods of diabetes detection are often inaccurate and invasive. Machine learning / AI offers a promising solution for the early detection of diabetes. Machine learning algorithms can automatically detect patterns in data and use those patterns to make predictions. Machine learning is well suited for the detection of diabetes because it can handle the large amount of data required for accurate predictions. In addition, machine learning algorithms can automatically identify patterns that are too subtle for humans to discern. Quick Overview on Machine …
Healthcare Claims Processing AI Use Cases
In recent years, artificial intelligence (AI) / machine learning (ML) has begun to revolutionize many industries – and healthcare is no exception. Hospitals and insurance companies are now using AI to automate various tasks in the healthcare claims processing workflow. Claims processing is a complex and time-consuming task that often requires manual intervention. By using AI to automate claims processing, healthcare organizations can reduce costs, improve accuracy, and speed up the claims adjudication process. In this blog post, we will explore some of the most common use cases for healthcare claims processing AI / machine learning. Automated Data Entry One of the most time-consuming tasks in the claims process is …
Top Healthcare Data Aggregation Companies
Data aggregation is the process of collecting data from multiple sources and compiling it into a single database. This process is essential for healthcare professionals, companies and startups because it allows them to track and analyze patient data, which can be used to improve patient care. There are many companies that offer healthcare data aggregation services. However, not all of them are created equal. To help you choose the right company for your needs, we’ve compiled the following list of the top healthcare data aggregation companies. This list will be updated from time-to-time. Athenahealth: Athenahealth is a healthcare data aggregation company that provides electronic health records, practice management software, and …
Healthcare & Machine Learning Use Cases / Projects
AI & Machine learning is being used more and more in the healthcare industry. This is because it has the potential to improve patient outcomes, make healthcare more cost-effective, and help with other important tasks. In this blog post, we will discuss some of the healthcare & AI / machine learning use cases that are currently being implemented. We will also talk about the benefits of using machine learning in healthcare settings. Stay tuned for an exciting look at the future of healthcare! What are top healthcare challenges & related AI / machine learning use cases? Before getting into understand how machine learning / AI can be of help in …
Artificial Intelligence (AI) for Telemedicine: Use cases, Challenges
In this post, you will learn about different artificial intelligence (AI) use cases of Telemedicine / Telehealth including some of key implementation challenges pertaining to AI / machine learning. In case you are working in the field of data science / machine learning, you may want to go through some of the challenges, primarily AI related, which is thrown in Telemedicine domain due to upsurge in need of reliable Telemedicine services. What is Telemedicine? Telemedicine is the remote delivery of healthcare services, using digital communication technologies. It has the potential to improve access to healthcare, especially in remote or underserved communities. It can be used for a variety of purposes, including …
Digital Healthcare Technology & Innovations: Examples
Digital healthcare technology is making waves in the medical community. It has the potential to change the way we approach healthcare, and it is already starting to revolutionize the way patients are treated. In this blog post, we will explore some of the most exciting digital healthcare technologies including AI / machine learning & blockchain based applications, initiatives and innovations. We will also take a look at some real-world examples of how these technologies are being used to improve patient care. Digital health refers to the use of digital technology to improve the delivery of healthcare services. Connected health (also known as i-health) is a term that encompasses all digital …
Free MIT Course on Machine Learning for Healthcare
In this post, you will get a quick overview on free MIT course on machine learning for healthcare. This is going to be really helpful for machine learning / data science enthusiasts as building machine learning solutions to serve healthcare requirements comes with its own set of risks. It will be good to learn about different machine learning techniques, applications related disease progression modeling, cardiac imaging, pathology etc, risks and risk mitigation techniques. Here is the link to the course – Machine Learning for Healthcare Here are the links to some of the important course content: Video lectures Lecture notes (PDF) The entire course material can be downloaded from this page – …
Obamacare Website HealthCare.gov & Security Threats Review
Well, there have been lot of discussions around security issues with Obamacare website, healthcare.gov which has become talk of the town recently. The federal portal serves 36 states not operating their own health insurance exchanges. Fourteen other states and the District of Columbia run their own marketplaces. One of the factors attributing to security issues is sheer large volume of untested source code covering 500 millions lines of code. One of the most important security threat is related with information disclosure of the millions of Americans. The sensitive personal information of millions of Americans such as social security numbers (SSN), birthdays, incomes, home mortgages, and addresses is at risk. Another security …
I found it very helpful. However the differences are not too understandable for me