Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry.

Artificial intelligence (AI) is a reality of our times, and it has been successfully implemented in all fields, including medicine. As a relatively new domain, all efforts are directed towards creating algorithms applicable in most medical specialties. Pathology, as one of the most important areas of interest for precision medicine, has received significant attention in the development and implementation of AI algorithms. This focus is especially important for achieving accurate diagnoses. Moreover, immunohistochemistry (IHC) serves as a complementary diagnostic tool in pathology. It can be further augmented through the application of deep learning (DL) and machine learning (ML) algorithms for assessing and analyzing immunohistochemical markers. Such advancements can aid in delineating targeted therapeutic approaches and prognostic stratification. This article explores the applications and integration of various AI software programs and platforms used in immunohistochemical analysis. It concludes by highlighting the application of these technologies to pathologies such as breast, prostate, lung, melanocytic proliferations, and hematologic conditions. Additionally, it underscores the necessity for further innovative diagnostic algorithms to assist physicians in the diagnostic process.

Chromophobe renal cell carcinoma with massive sarcomatoid differentiation.

Chromophobe renal cell carcinoma (CRCC) is a distinct subtype of renal cell carcinoma with unique histological, immunohistochemical, cytogenetic, and ultrastructural features, which usually has a favorable clinical course, with only a small percentage of patients developing recurrence, metastasis, or death due to its complications. Sarcomatoid differentiation can occur in any subtype of renal cell carcinoma and currently represents the transformation into a higher degree of malignancy, its presence being associated with a reserved prognosis, with a reported incidence of average survival of less than 1 year after diagnosis. In this study, we present an unusual case of CRCC with massive sarcomatoid differentiation, which infiltrated the left adrenal gland and was surgically resected. The histological features of this tumor as well as a brief review of literature are presented.

Advancing Patient Care: How Artificial Intelligence Is Transforming Healthcare.

Artificial Intelligence (AI) has emerged as a transformative technology with immense potential in the field of medicine. By leveraging machine learning and deep learning, AI can assist in diagnosis, treatment selection, and patient monitoring, enabling more accurate and efficient healthcare delivery. The widespread implementation of AI in healthcare has the role to revolutionize patients' outcomes and transform the way healthcare is practiced, leading to improved accessibility, affordability, and quality of care. This article explores the diverse applications and reviews the current state of AI adoption in healthcare. It concludes by emphasizing the need for collaboration between physicians and technology experts to harness the full potential of AI.

Suicide during COVID-19 infection - Case report and literature review

ABSTRACT The COVID-19 pandemic has a global effect on people's mental health. The SARS-CoV-2 infection is a new source of anxiety, depression, and psycho-emotional changes in people without morbid conditions, with even more important impact on patients with associated diseases. We present the case of a previously diagnosed patient with COVID-19, in which the psychological effects accumulated during hospitalization triggered an autolytic behaviour. The case presented by us and the review of the literature show that serious diseases are frequently associated with depression and emotional disorders, and SARS-CoV-2 infection is no exception

Consent for participating in clinical trials - Is it really informed?

The article explores the challenges of ensuring voluntary and informed consent which is obtained from potential research subjects in the north-eastern part of Romania. This study is one of the first empirical papers of this nature in Romania. The study used a quantitative survey design using the adapted Quality of Informed Consent (QuIC) questionnaire. The target population consisted of 100 adult persons who voluntarily enrolled in clinical trials. The informed consent form must contain details regarding the potential risks and benefits, the aim of the clinical trial, study design, confidentiality, insurance and contact details in case of additional questions. Our study confirmed that although all required information was included in the ICF, few clinical trial participants truly understood it. We also found that the most important predictive factor for a good subjective and objective understanding of the clinical trial was the level of education. Our study suggests that researchers should consider putting more effort in order to help clinical trials participants achieve a better understanding of the informed consent. In this way they will ensure that participants' decision-making is meaningful and that their interests are protected.