Artificial intelligence in medical imaging: threat or opportunity? : radiologists again at the forefront of innovation in medicine

One of the most promising areas of health innovation is the application of artificial intelligence (AI), primarily in medical imaging. This article provides basic definitions of terms such as "machine/deep learning" and analyses the integration of AI into radiology. Publications on AI have drastically increased from about 100-150 per year in 2007-2008 to 700-800 per year in 2016-2017. Magnetic resonance imaging and computed tomography collectively account for more than 50% of current articles. Neuroradiology appears in about one-third of the papers, followed by musculoskeletal, cardiovascular, breast, urogenital, lung/thorax, and abdomen, each representing 6-9% of articles. With an irreversible increase in the amount of data and the possibility to use AI to identify findings either detectable or not by the human eye, radiology is now moving from a subjective perceptual skill to a more objective science. Radiologists, who were on the forefront of the digital era in medicine, can guide the introduction of AI into healthcare. Yet, they will not be replaced because radiology includes communication of diagnosis, consideration of patient's values and preferences, medical judgment, quality assurance, education, policy-making, and interventional procedures. The higher efficiency provided by AI will allow radiologists to perform more value-added tasks, becoming more visible to patients and playing a vital role in multidisciplinary clinical teams

A short history of tattoo

Tattoo is a permanent pigmentation of the skin resulting from the introduction of exogenous substances. If this happens unintentionally\u2014for example, after road injuries\u2014it is called traumatic tattoo. However, the most common tattoos are decorative, related to current fashion or to a symbolic meaning. The etymological origin of the word tattoo is believed to have 2 major derivations: the first is from the Polynesian word \u201cta\u201d which means \u201cstriking something,\u201d and the second is the Tahitian word \u201ctatau\u201d which means \u201cto mark something.\u201d This word was introduced in Europe by the English explorer James Cook, who described the Polynesian technique of \u201ctattaw\u201d in his narrative of the voyage

The Use of Artificial Intelligence (AI) in the Radiology Field: What Is the State of Doctor–Patient Communication in Cancer Diagnosis?

Simple Summary Artificial Intelligence (AI) has been increasingly used in radiology to improve diagnostic procedures over the past decades. The application of AI at the time of cancer diagnosis also creates challenges in the way doctors should communicate the use of AI to patients. The present systematic review deals with the patient's psycho-cognitive perspective on AI and the interpersonal skills between patients and physicians when AI is implemented in cancer diagnosis communication. Evidence from the retrieved studies pointed out that the use of AI in radiology is negatively associated with patient trust in AI and patient-centered communication in cancer disease. Background: In the past decade, interest in applying Artificial Intelligence (AI) in radiology to improve diagnostic procedures increased. AI has potential benefits spanning all steps of the imaging chain, from the prescription of diagnostic tests to the communication of test reports. The use of AI in the field of radiology also poses challenges in doctor-patient communication at the time of the diagnosis. This systematic review focuses on the patient role and the interpersonal skills between patients and physicians when AI is implemented in cancer diagnosis communication. Methods: A systematic search was conducted on PubMed, Embase, Medline, Scopus, and PsycNet from 1990 to 2021. The search terms were: ("artificial intelligence" or "intelligence machine") and "communication" "radiology" and "oncology diagnosis". The PRISMA guidelines were followed. Results: 517 records were identified, and 5 papers met the inclusion criteria and were analyzed. Most of the articles emphasized the success of the technological support of AI in radiology at the expense of patient trust in AI and patient-centered communication in cancer disease. Practical implications and future guidelines were discussed according to the results. Conclusions: AI has proven to be beneficial in helping clinicians with diagnosis. Future research may improve patients' trust through adequate information about the advantageous use of AI and an increase in medical compliance with adequate training on doctor-patient diagnosis communication

A case of acquired tufted angioma in adulthood

Tufted angioma is a rare vascular tumor whose name derives from its histopathological appearance, characterized by tufts of capillaries within the dermis. Its etiology and pathogenesis are uncertain. Tufted an\uc2\uadgioma typically occurs during infancy or early childhood and displays various clinical patterns. It may present as a subtle stain-like area that later thickens as a large plaque, infiltrated or dusky blue-purple lesion, or as an exophytic, firm, violaceous, cutaneous nodule. Medical treatment is not necessary for tufted angioma, given its benign nature and slow progression. Only clinical follow-up is therefore recommended