Medical problem solving

BACKGROUND: Reducing proton treatment time improves patient comfort and decreases the risk of error from intrafractional motion, but must be balanced against clinical goals and treatment plan quality. PURPOSE: To improve the delivery efficiency of spot scanning proton therapy by simultaneously reducing the number of spots and energy layers using the reweighted <mml:math xmlns:mml="https://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:msub><mml:mi>l</mml:mi> <mml:mn>1</mml:mn></mml:msub> <mml:annotation>$l_1$</mml:annotation></mml:semantics> </mml:math> regularization method...

PURPOSE: In many countries, outpatient and inpatient care are separated. During hospitalization, therefore, switching the outpatient medication to medication of the hospital formulary is required. METHODS: We newly designed a switching algorithm in six switching steps (S0-S5) and conducted a study at Bundeswehr Hospital Hamburg (300 beds, 80% civilians). We performed (i) a medication reconciliation to obtain information on outpatient medications and (ii) a medication review to solve drug-related-problems, e...

Ordinal response is commonly found in medicine, biology, and other fields. In many situations, the predictors for this ordinal response are compositional, which means that the sum of predictors for each sample is fixed. Examples of compositional data include the relative abundance of species in microbiome data and the relative frequency of nutrition concentrations. Moreover, the predictors that are strongly correlated tend to have similar influence on the response outcome. Conventional cumulative logistic regression models for ordinal responses ignore the fixed-sum constraint on predictors and their associated interrelationships, and thus are not appropriate for analyzing compositional predictors...

Chimeric Antigen Receptor T cell (CAR-T) therapy has revolutionized cancer treatment, but its application to solid tumors is limited. CAR-T cells have poor incapability of entering, surviving, proliferating, and finally exerting function in the tumor microenvironment. This review summarizes the main strategies related to enhancing the infiltration, efficacy, antigen recognition, and production of CAR-T in solid tumors. Additional applications of CAR-γδ T and macrophages are also discussed. We believe CAR-T will be a milestone in treating solid tumors once these problems are solved...

BACKGROUND: Medical school curricula strive to train community-engaged and culturally competent physicians, and many use service learning to instill these values in students. The current standards for medical service learning frameworks have opportunities for improvement, such as encouraging students to have more sustainable and reciprocal impact and to ingrain service learning as a value to carry throughout their careers rather than a one-time experience. PEDS 220: A COVID-19 Elective is a Stanford University course on the frontlines of this shift; it provides timely education on the COVID-19 pandemic, integrating community-oriented public health work to help mitigate its impact...

BACKGROUND: Liver lesions mainly occur inside the liver parenchyma, which are difficult to locate and have complicated relationships with essential vessels. Thus, preoperative planning is crucial for the resection of liver lesions. Accurate segmentation of the hepatic and portal veins (PVs) on computed tomography (CT) images is of great importance for preoperative planning. However, manually labeling the mask of vessels is laborious and time-consuming, and the labeling results of different clinicians are prone to inconsistencies...

Medical image fusion can provide doctors with more detailed data and thus improve the accuracy of disease diagnosis. In recent years, deep learning has been widely used in the field of medical image fusion. The traditional method of medical image fusion is to operate by superimposing and other methods of pixels. The introduction of deep learning methods has improved the effectiveness of medical image fusion. However, these methods still have problems such as edge blurring and information redundancy. In this paper, we propose a deep learning network model based on Transformer and an improved DenseNet network module integration that can be applied to medical images and solve the above problems...

Vascular structure segmentation in intravascular ultrasound (IVUS) images plays an important role in pre-procedural evaluation of percutaneous coronary intervention (PCI). However, vascular structure segmentation in IVUS images has the challenge of structure-dependent distractions. Structure-dependent distractions are categorized into two cases, structural intrinsic distractions and inter-structural distractions. Traditional machine learning methods often rely solely on low-level features, overlooking high-level features...

This paper presents a novel method based on leveraging physics-informed neural networks for magnetic resonance electrical property tomography (MREPT). MREPT is a noninvasive technique that can retrieve the spatial distribution of electrical properties (EPs) of scanned tissues from measured transmit radiofrequency (RF) in magnetic resonance imaging (MRI) systems. The reconstruction of EP values in MREPT is achieved by solving a partial differential equation derived from Maxwell's equations that lacks a direct solution...

Globally, traffic accidents on the highway network contribute significantly to a high fatality rate, drawing considerable attention from health institutions. The efficiency of transportation plays a vital role in mitigating the severe consequences of these incidents. This study delves into the issues of emergency vehicles experiencing delays despite having priority. Therefore, we construct mixed-integer linear programming with semi-soft time windows (MIPSSTW) model for optimizing emergency vehicle routing in highway incidents...

INTRODUCTION: International research suggests that poor patient compliance is the main cause of tutor failures in the context of potential novel orthopedic bivalve braces for conservative treatment of pectus carinatum. Our entire experimental study is based on the hypothesis that a rigid bivalve brace that patients can accept could solve the main problem associated with the conservative approach-poor compliance. The hypothesis was to reduce the thickness and weight of the classic bivalve brace to ensure concealment and make it sustainable enough to be worn several hours a day without compromising its therapeutic efficacy...

BACKGROUND: In this paper, we look at how to design and build a system to find tumors using 2 Convolutional Neural Network (CNN) models. With the help of digital image processing and deep Learning, we can make a system that automatically diagnoses and finds different diseases and abnormalities. The tumor detection system may include image enhancement, segmentation, data enhancement, feature extraction, and classification. These options are set up so that the CNN model can give the best results...

BACKGROUND: Fundus photography is the most important examination in eye disease screening. A facilitated self-service eye screening pattern based on the fully automatic fundus camera was developed in 2022 in Shanghai, China; it may help solve the problem of insufficient human resources in primary health care institutions. However, the service quality and residents' preference for this new pattern are unclear. OBJECTIVE: This study aimed to compare the service quality and residents' preferences between facilitated self-service eye screening and traditional manual screening and to explore the relationships between the screening service's quality and residents' preferences...

BACKGROUND: Moral distress has negative effects on physical and mental health. However, there is little information about nurses' coping strategies reducing moral distress. AIM: The purpose of this study was to investigate the coping strategies of intensive care unit nurses reducing moral distress in Iran. STUDY DESIGN: This is a qualitative study with a content analysis approach. PARTICIPANTS AND RESEARCH CONTEXT: The research sample consisted of nurses working in intensive care units of teaching hospitals affiliated to Tehran University of Medical Sciences...

Processing of Chinese medicinal materials is an important part in the Chinese medicine heritage, and the temperature control in the processing has a direct impact on the quality and efficacy of traditional Chinese medicines. However, the processing of Chinese medicinal materials has the problems of subjective temperature judgement, determination of the end point based on experience, unclear processing mechanism, unstable quality of products, and inconsistent processing standards. The temperature control in the processing is reflected in the appearance and internal quality of Chinese medicinal materials...

The Iterative Close Point (ICP) algorithm is used for bone registrations based on ultrasound measurements. However, the ICP has been shown to suffer from local minima. The Complex optimization, as a more robust routine compared to the commonly used gradient-based algorithms, could be an alternative for solving the ICP problem. In this study, we investigated the effect of the initial estimate and the number of registration points on bone registrations achieved using the ICP and a Complex optimization routine and we compared it against using Quadratic Sequential Programming (SQP)...

Bacterial infection remains a significant problem associated with orthopaedic surgeries leading to surgical site infection (SSI). This unmet medical need can become an even greater complication when surgery is due to malignant bone tumor. In the present study, we evaluated in vitro titanium (Ti) implants subjected to gallium (Ga) and silver (Ag)-doped thermochemical treatment as strategy to prevent SSI and improve osteointegration in bone defects caused by diseases such as osteoporosis, bone tumor, or bone metastasis...

Whole Genome Duplications (WGDs) are events that double the content and structure of a genome. In some organisms, multiple WGD events have been observed while loss of genetic material is a typical occurrence following a WGD event. The requirement of classic rearrangement models that every genetic marker has to occur exactly two times in a given problem instance, therefore, poses a serious restriction in this context. The Double - Cut and Join (DCJ) model is a simple and powerful model for the analysis of large structural rearrangements...

In view of the spread of corona virus disease 2019 (COVID-19), this paper proposes a fractional-order generalized SEIR model. The non-negativity of the solution of the model is discussed. Based on the established threshold <mml:math xmlns:mml="https://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>R</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math>, the existence of the disease-free equilibrium and endemic equilibrium is analyzed. Then, sufficient conditions are established to ensure the local asymptotic stability of the equilibria...

Dementia, an increasingly prevalent neurological disorder with a projected threefold rise globally by 2050, necessitates early detection for effective management. The risk notably increases after age 65. Dementia leads to a progressive decline in cognitive functions, affecting memory, reasoning, and problem-solving abilities. This decline can impact the individual's ability to perform daily tasks and make decisions, underscoring the crucial importance of timely identification. With the advent of technologies like computer vision and deep learning, the prospect of early detection becomes even more promising...