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Rationale and Objectives This study aimed to provide decision support for the human expert, to categorize liver metastases into their primary cancer sites. Currently, once a liver metastasis is detected, the process of finding the primary site is challenging, time-consuming, and requires multiple examinations. The proposed system can support the human expert in localizing the search for the cancer source by prioritizing the examinations to probable cancer sites. Materials and Methods The suggested method is a learning-based approach, using computed tomography (CT) data as the input source. Each metastasis is circumscribed by a radiologist in portal phase and in non-contrast CT images. Visual features are computed from these images, combined into feature vectors, and classified using support vector machine classification. A variety of different features were explored and tested. A leave-one-out cross-validation technique was conducted for classification evaluation. The methods were developed on a set of 50 lesion cases taken from 29 patients. Results Experiments were conducted on a separate set of 142 lesion cases taken from 71 patients with four different primary sites. Multiclass categorization results (four classes) achieved low accuracy results. However, the proposed system was found to provide promising results of 83% and 99% for top-2 and top-3 classification tasks, respectively. Moreover, when compared to the experts' ability to distinguish the different metastases, the system shows improved results. Conclusions Automated systems, such as the one proposed, show promising new results and demonstrate new capabilities that, in the future, will be able to provide decision and treatment support for radiologists and oncologists, toward more efficient detection and treatment of cancer. [ABSTRACT FROM AUTHOR]

This article, published in the journal Allergy, discusses a study that explores the existence of different subtypes of asthma based on immune signaling pathways. The study recruited 200 asthmatic patients and measured levels of certain cytokines in their sputum. The results revealed two distinct pathways of immune signaling, each associated with different patterns of cytokine expression. One pathway was linked to more severe disease and frequent hospitalizations. The study suggests that understanding these subtypes could lead to more targeted treatments for asthma. However, further research is needed to confirm these findings. The article also includes a table with various data points related to asthma patients, providing valuable information for research purposes. [Extracted from the article]

Percutaneous dilatational tracheostomy is a minimally invasive procedure performed for those who require prolonged mechanical ventilation. It is a procedure that is performed routinely at the bedside in the intensive care unit. Complications nonetheless still occur, and as a result, several technique modifications have been employed. At Loma Linda University Medical Center, we have implemented a novel technique using augmented reality during percutaneous dilatational tracheostomy placement in an attempt to minimize such complications. Using Brother's AiRScouter WD-200B head mounted display, the tracheostomy operator is able to focus on the surgical field without having to significantly break line of sight to view the traditional bronchoscopy monitor. Six cases have been treated with this procedure to date with good success and excellent user feedback. We aim to assess augmented reality-assisted percutaneous dilatational tracheostomy and determine its overall efficacy when compared to traditional percutaneous dilatational tracheostomy. [ABSTRACT FROM AUTHOR]

We report and discuss five patients with intracranial hypertension due to a skull lesion reducing cerebral sinus patency with a compressive, non-thrombotic mechanism. We illustrate the importance of a high level of suspicion for this condition in patients presenting with headache, papilledema and increased intracranial pressure in the absence of focal signs or radiological evidence of mass effect. [ABSTRACT FROM AUTHOR]