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AI vs Human: How to read an X-ray like a pro

In today’s blog post we will learn what are the steps that a radiologist follows when he does a chest radiography for a patient who may be coming for pulmonary problems.  
It is the most common diagnostic visualization technique used to assess respiratory issues. Its popularity comes from a number of variables, including the fact that it is inexpensive, quick, and simple to conduct, produces almost no irradiation, and is both accessible and feasible to patients and doctors.

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Pleural effusion: why we need to diagnose it earlier

Pleurisy is an inflammatory condition in pulmonology, with more than 50 recognized causes, including pleural or lung lesions, systemic diseases, organ dysfunction and medication. Pleural effusion represents the abnormal accumulation of fluid in the space between the lungs and the rib cage, called the pleural space. Normally, this area contains only a thin amount of fluid, which aids the movement of the lungs during breathing.

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Is it ethical to use AI in healthcare?

Artificial general intelligence has numerous advantages. It has the potential to transform both public and private operations. Recognition software, for example, is excellent news for healthcare: it can aid in the diagnosis of diseases including cancer and early onset dementia. However, such mainstream AI uses demonstrate how this emerging technology presents moral considerations.

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Machine learning for beginners

Machine learning is playing an increasingly essential role in the field of medical imaging. It includes problems as diverse as computer-assisted diagnosis, lesion detection, segmentation of anatomical regions of interest, brain mapping, image-guided therapy, image annotation, and database retrieval.
According to Peter Eggleston, global marketing director for GE Healthcare, “AI is making radiology professionals more productive, boosting quantity, and enhancing the precision of their work.”

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Artificial Intelligence is helping lung cancer detection 

Mankind is facing a critical health problem: in the coming decades, cancer will become the world’s most important disease. 2023 is expected to be the year in which cancer will overcome all cardiovascular diseases, becoming the number one killer, with a tendency to double the number of cases and deaths in 2030.

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How Artificial Intelligence improves Healthcare 

Information has showed to be an essential factor in enhancing the results of illness. Machine learning, or the analysis of huge datasets, its interpretation, and sophisticated computer algorithms, is now becoming a cornerstone for gaining ground and progress in the medical industry. Data is the golden ticket to democratizing and personalizing treatment through digital health.

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Machines can see things we cannot see

From the beginning of time, medicine was based on evidence. Even if societies have changed their approach towards illness and disease from ancient times until the present, one thing remains valid: the ability to see the the pathological process that underlies the condition is an asset for treating it.  At first, doctors could only use […]

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How an AI-based software for medical imaging diagnosis could be a learning tool for young doctors

Analyzing and interpreting medical images is not an easy job, it requires highly developed skills and years of practice. In Romania, the young doctors that are choosing radiology as a further specialization need to finalize a 4-year medical residency before obtaining a full license to practice medicine as medical image specialists. Usually, they are doing […]

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How Artificial Intelligence helps doctors in screening, triaging, and analyzing patients in one of the largest medical institutions in Western Romania

Timișoara County Hospital is one of the largestt and most advanced medical institutions in Western Romania, accounting for a large flow of interregional patients. On a daily basis, thousands of patients are coming to this medical institution, and several hundred of them reach the medical imaging department. This department is analyzing an increasingly large number […]

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