How an AI platform could help create better Screening Campaigns

The majority of global disease burden and mortality are caused by non-communicable diseases. However, a sizable portion of patients in both high-income nations and low-income and middle-income countries are still uninformed that they have these life threatening illnesses.

Many diagnostic systems are extremely costly, invasive, or need skilled healthcare professionals to operate, making their use in environments with limited resources impossible.
AI software for lung nodule evaluation utilizing deep learning (DL) could be able to recognize certain patterns in imaging data and provide outstanding results.

The Complete Guide to Lung Cancer Detection and How AI could Improve Outcomes

Lung cancer is the most common cancer-related cause of death for both men and women, killing more than 1 million people annually. More individuals pass away from it than from the combined deaths from the next three major types of cancer: breast, colon, and prostate cancer.
Unfortunately, it has a poor prognosis despite improvements in surgical methods and combination therapy. Recent developments in medical imaging technology, such as CT nodules detections through AI algorithms, have made it possible to create 3D images that are more comprehensive. This allows for improved evaluation of a lesion’s evolution using comparison-based automated measures.

Evaluation of Patients with Pulmonary Nodules

One of the most frequent causes for patient referrals for pulmonary examination is the presence of lung nodules.

XVision’s software offers a recognition algorithm that enables radiologists to detect lung nodules and display them using an easy-to-read User-Interface, allowing higher accuracy in a shorter amount of time.

Human vs AI: How to Read a CT Scan like a pro 

In today’s blog post, we’ll continue the pulmonary medical imaging lesson that a radiologist learns for doing a chest computed tomography on a patient who may be experiencing lung issues.

CT is still the most commonly utilized and reviewed cross-sectional scanning technology for the thorax, and it is continuously evolving. Thoracic CT imaging techniques are adjusted to the clinical question and the structures of interest, much like any other imaging procedure.