How to develop an AI medical imaging platform

When thinking about the clinical validation of a medical system, one of the first factors that must be considered is how the system will be integrated into the clinical workflow.

In the initial years, software systems were mostly embedded in hardware medical devices, and thus the primary concern was guarding against the possibility of physical harm, with attention to aspects such as the transmission of energy and/or substances to or from the body, the degree of invasiveness, the closeness to sensitive organs, etc.
This was reflected in many of the regulatory directives and guidelines, which often did not offer specific indications for software developed as a standalone clinical aid. As the use of such applications steadily grew, the need for specific guidance was felt and several contributions were developed.

Why are doctors afraid of AI? 

Artificial intelligence (AI) technology has advanced extremely fast in the last years, owing in great part to breakthroughs in machine learning, which is closely tied to data science and statistical prediction. Modeling is involved across several elements of the health sector, including diagnosing, treatment, management, and logistics. Because of the link between machine learning’s capabilities and the needs of the health-care space, it’s widely assumed that AI will have a significant impact.

Pulmonary edema and early detection with XVision

Pulmonary edema, also known as pulmonary congestion, is excessive liquid accumulation in the tissue and air spaces (usually alveoli) of the lungs. It causes poor oxygen delivery, which can lead to hypoxemia and respiratory failure. It occurs when the left ventricle of the heart fails to appropriately remove oxygenated blood from the pulmonary circulation (cardiogenic pulmonary edema), or when lung tissue or blood vessels are injured directly (non-cardiogenic pulmonary edema)

Teleradiology: the next step in smart healthcare 

One of the most difficult problems we are currently experiencing is figuring out how to manage remote workforces. Because the largest portion of IT enterprises operate remotely, the IT sector has emerged as a leading model for the rest of the globe. However, due to the pandemic’s obstacles, a substantial number of organizations are fighting to stay afloat, the medical field being of them. 

There is a contrast enhanced CT shortage and AI could solve it 

Contrast CT, or contrast enhanced computed tomography (CECT), is a form of X-ray computed tomography using radiocontrast (substance that is injected into the body to allow the visualization of special structures such as blood vessels). Radiocontrast for CT is made generally from iodine-based compounds. This is important for highlighting features that are too difficult to distinguish from […]