Army Urban Augmentation Medical Task Forces for COVID-19: Part 1—Development

ABSTRACT This article describes how the U.S. Army developed a new ad hoc medical formation, named Urban Augmentation Medical Task Force for the Department of Defense (DoD) in response to the Coronavirus Disease 2019 pandemic in the Continental United States during the spring of 2020. We review the role of the DoD support of the Federal Emergency Management Agency as a part of Defense Support of Civilian Authorities.

Army Urban Augmentation Medical Task Forces for COVID-19: Part 2—Initial Utilization

ABSTRACT This article describes the utilization of a new ad hoc medical formation, named Urban Augmentation Medical Task Force for the Department of Defense response to the coronavirus disease 2019 pandemic in the Continental United States during the spring of 2020. Military medical personnel from these units were used to staff a variety of different mission assignments. We review the benefits and limitation of this type of formation and recommend future force allocation models.

Recent advances in diagnostic and therapeutic approaches for breast cancer: A comprehensive review

: A silent monster breast cancer is a challenging medical task for researchers. Breast cancer is a leading cause of death in women related to other cancers. A case of breast cancer is diagnosed among women every 19 seconds, and every 74 seconds a women dies of breast cancer somewhere in the world. Several risk factors such as genetic and environmental factors favor breast cancer development. This review tends to provide deep understandings regarding the genetics of breast cancer along with multiple diagnostic and therapeutic approaches as problem-solving negotiators to switch off the progression of breast cancer. This assembled data mainly aims to discuss omics-based approaches to provide enthralling diagnostic biomarkers and emerging novel therapies to combat breast cancer. This review article intends to pave a new path for the discovery of effective treatment options.

Bladder Semantic Segmentation

Obtaining information about the shape and volume of the bladder plays a significant role in determining the pathologies of this organ. To collect the relevant data, the first thing to do is to separate the bladder from the background on the ultrasound image. The article is devoted to automation this process using an algorithm based on the Unet architecture with a pretrained imagenet encoder (encoder – ResNet50). The article gives a comparative analysis of some well-known methods in the literature that improve the accuracy of the proposed algorithm. The quality of the basic architecture has been improved by more than 4 percent on the PR AUC metric (from 84.49% to 89.62%) in the series of experiments with the help of automatic annotation of previously unmarked data. In addition, there are two important results showing practical effectiveness of using the data from another medical task (which raised the accuracy to 88.50%) and using time-dependent sequence of frames inside the video (raised the quality to 88.19%).

Public Health Academic Alliance for COVID-19 Response: The Role of a National Medical Task Force in Puerto Rico

Alliances between the government and academic communities can be a key component of the public health response to an emergency such as the coronavirus disease 2019 (COVID-19) pandemic. The Governor of Puerto Rico designated the Puerto Rico Medical Task Force (MTF) COVID-19 to provide direct guidance and evaluation of the government response to the epidemic in Puerto Rico. Several work groups were formed within the MTF to create protocols and provide evidence-based recommendations on different public health aspects. The collaboration between the academia and the government enhanced the Puerto Rican public health response and contributed to the reduction seen in the contagion curve. Healthcare services and hospitals have not reached their maximum patient care capacity and the death toll has been controlled. Incorporating a national MTF with members of the academia into the government structure was beneficial during the COVID-19 response in Puerto Rico. A similar strategy could serve as a model for other states or territories and countries in similar scenarios.

Dissemination of Genetic Information in Swiss Families with Lynch Syndrome: A Qualitative Exploratory Study

In Switzerland, out of respect for privacy and in accordance with federal laws regarding genetic testing, information sharing about hereditary cancer predisposition syndromes is initiated solely by the proband and never from the medical clinic. Thus, an essentially medical task, communication of cancer risk and possible testing, is always delegated, at least initially, to the patient. In order to explore this communication process, its associated difficulties and possibilities for improvements, we have conducted a study with Lynch syndrome families in Western Switzerland. Semi-structured interviews were conducted with 19 participants (12 female, 7 male), either in person or by telephone. We specifically explored whether participants considered transmission of genetic information a medical or personal responsibility. Other recurrent themes were also identified, including family wisdom and superstitions, emotional responses, and parent-child guilt. The identification of a cancer predisposition and the request to communicate this with family members remained a traumatic experience for many. However, within this group, which may be biased towards better communicators, the information was shared with at risk relatives. Despite inherent difficulties, the majority wish to retain the responsibility for contacting family members. This suggests that in Switzerland, and possibly in other countries with similar rules/attitudes towards privacy, efforts to improve cascade screening should be directed towards facilitating intra-familial communication.

A question-entailment approach to question answering

Background One of the challenges in large-scale information retrieval (IR) is developing fine-grained and domain-specific methods to answer natural language questions. Despite the availability of numerous sources and datasets for answer retrieval, Question Answering (QA) remains a challenging problem due to the difficulty of the question understanding and answer extraction tasks. One of the promising tracks investigated in QA is mapping new questions to formerly answered questions that are “similar”. Results We propose a novel QA approach based on Recognizing Question Entailment (RQE) and we describe the QA system and resources that we built and evaluated on real medical questions. First, we compare logistic regression and deep learning methods for RQE using different kinds of datasets including textual inference, question similarity, and entailment in both the open and clinical domains. Second, we combine IR models with the best RQE method to select entailed questions and rank the retrieved answers. To study the end-to-end QA approach, we built the MedQuAD collection of 47,457 question-answer pairs from trusted medical sources which we introduce and share in the scope of this paper. Following the evaluation process used in TREC 2017 LiveQA, we find that our approach exceeds the best results of the medical task with a 29.8% increase over the best official score. Conclusions The evaluation results support the relevance of question entailment for QA and highlight the effectiveness of combining IR and RQE for future QA efforts. Our findings also show that relying on a restricted set of reliable answer sources can bring a substantial improvement in medical QA.