Case Based Learning

PURPOSE: Diversity, equity, and inclusion (DEI) have become an important priority for academic medicine. However, several barriers challenge the effective implementation of DEI-related pedagogy. An exploration of the barriers to and enablers of DEI-related pedagogy-as they relate to professional contexts-can inform how to advance DEI in medical education. Shulman's notion of signature pedagogies offers a foundation for understanding and exploring the influence of such contexts on teaching and learning...

First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be hard to build and expensive to simulate for complex living systems. On the other hand, modern data-driven methods thrive at modeling many types of high-dimensional and noisy data. Still, the training and interpretation of these data-driven models remain challenging. Here, we combine the two types of methods to model stochastic neuronal network oscillations...

Background: The severity of antipsychotic-induced cervical dystonia has traditionally been evaluated visually. However, recent advances in information technology made quantification possible in this field through the introduction of engineering methodologies like machine learning. Methods: This study was conducted from June 2021 to March 2023. Psychiatrists rated the severity of cervical dystonia into 4 levels (0: none, 1: minimal, 2: mild, and 3: moderate) for 101 videoclips, recorded from 87 psychiatric patients receiving antipsychotics...

BACKGROUND: Zimbabwean government adopted competency-based curriculum in 2017 as a measure to prepare learners for life and work in an indigenised economy and increasingly globalised and competitive environment. The government also sought to ensure that learners develop skills necessary for lifelong learning in line with the emerging opportunities. OBJECTIVES: The purpose of this study was to explore challenges faced by teachers in the implementation of competency-based curriculum to learners with learning disabilities in Mhangura of Makonde District in Zimbabwe...

INTRODUCTION: Cyberbullying is a commonly-seen and hotly-debated social topic around the globe. This negative behavior is the source of many disastrous events, and so leading government bodies, organizations, schools and social communities attach great importance to addressing this topic. However, there is still much work to do in order to be clear about the causes of cyberbullying. METHODS: The previous research cases were mostly viewed from the victims' perspectives; however, there is no comprehensive understanding of the perpetrators' viewpoints...

BACKGROUND: Thyroid-associated ophthalmopathy (TAO) is the most prevalent autoimmune orbital condition, significantly impacting patients' appearance and quality of life. Early and accurate identification of active TAO along with timely treatment can enhance prognosis and reduce the occurrence of severe cases. Although the Clinical Activity Score (CAS) serves as an effective assessment system for TAO, it is susceptible to assessor experience bias. This study aimed to develop an ensemble deep learning system that combines anterior segment slit-lamp photographs of patients with facial images to simulate expert assessment of TAO...

INTRODUCTION: Integrating climate change and health into a medical school curriculum is critical for future physicians who will manage health crises caused by a rapidly changing climate. Although medical schools have increasingly included climate change in the curriculum, there remains a need to address the link between the climate crisis, environmental justice, and historical policies that shape environmental health disparities in local communities. METHODS: In academic years 2021-2022 (AY22) and 2022-2023 (AY23), second-year medical students participated in a 2...

BACKGROUND: Currently, the Accreditation Council of Graduate Medical Education requires time-based pediatric experiences for emergency medicine (EM) residents in both pediatric emergency medicine (PEM) and critical care settings. The American Board of Emergency Medicine has published the Model of the Clinical Practice of Emergency Medicine, which is a list of content an EM resident should learn. However, this list is large and without prioritization and therefore can be difficult to incorporate into time-limited curricula...

Protein kinases become an important source of potential drug targets. Developing new, efficient, and safe small-molecule kinase inhibitors has become an important topic in the field of drug research and development. In contrast with traditional wet experiments which are time-consuming and expensive, machine learning-based approaches for predicting small molecule inhibitors for protein kinases are time-saving and cost-effective, which are highly desired for us. However, the issue of sample scarcity (known active and inactive compounds are usually limited for most kinases) poses a challenge to the research and development of machine learning-based kinase inhibitors' active prediction methods...

BACKGROUND: Vascular surgery patients admitted to the hospital are often multimorbid. In case of questions regarding chronic medical problems different specialties are consulted, which leads to a high number of treating physicians and possibly contradicting recommendations. The General Practitioner´s (GP) view could minimize this problem. However, it is unknown for which medical problems a GP would be consulted and if regular GP-involvement during rounds would be considered helpful by the specialists...

Building trustworthy and transparent image-based medical artificial intelligence (AI) systems requires the ability to interrogate data and models at all stages of the development pipeline, from training models to post-deployment monitoring. Ideally, the data and associated AI systems could be described using terms already familiar to physicians, but this requires medical datasets densely annotated with semantically meaningful concepts. In the present study, we present a foundation model approach, named MONET (medical concept retriever), which learns how to connect medical images with text and densely scores images on concept presence to enable important tasks in medical AI development and deployment such as data auditing, model auditing and model interpretation...

Cancer of unknown primary (CUP) site poses diagnostic challenges due to its elusive nature. Many cases of CUP manifest as pleural and peritoneal serous effusions. Leveraging cytological images from 57,220 cases at four tertiary hospitals, we developed a deep-learning method for tumor origin differentiation using cytological histology (TORCH) that can identify malignancy and predict tumor origin in both hydrothorax and ascites. We examined its performance on three internal (n = 12,799) and two external (n = 14,538) testing sets...

PURPOSE: Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. METHODS: Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation...

OBJECTIVES: To build self-supervised foundation models for multicontrast MRI of the whole brain and evaluate their efficacy in assisting diagnosis of brain tumors. METHODS: In this retrospective study, foundation models were developed using 57,621 enhanced head MRI scans through self-supervised learning with a pretext task of cross-contrast context restoration with two different content dropout schemes. Downstream classifiers were constructed based on the pretrained foundation models and fine-tuned for brain tumor detection, discrimination, and molecular status prediction...

The association between parental burnout and perfectionism, and whether and to what extent it is mediated by self-compassion, in case of mothers of children with Specific Learning Disorder (SLD) were rarely investigated in the related literature. To fill the gap felt, the present study aimed at providing a model for self-compassion, parental burnout, and perfectionism. The participants were 305 mothers of children with SLD, from Hamedan province, Iran, who had been referred to the relevant treatment centers between 2020 and 2021...

BACKGROUND: Endoscopic surgery has shown promise in treating Spontaneous Intracerebral Hemorrhage (sICH), but its adoption in county-level hospitals has been hindered by the high level of surgical expertise required. METHODS: In this retrospective study at a county hospital, we utilized a Cumulative Sum (CUSUM) control chart to visualize the learning curve for two neurosurgeons. We compared patient outcomes in the learning and proficient phases, and compared them with expected outcomes based on ICH score and ICH functional outcome score, respectively...

BACKGROUND: Positron emission tomography (PET) is extensively employed for diagnosing and staging various tumors, including liver cancer, lung cancer, and lymphoma. Accurate subtype classification of tumors plays a crucial role in formulating effective treatment plans for patients. Notably, lymphoma comprises subtypes like diffuse large B-cell lymphoma and Hodgkin's lymphoma, while lung cancer encompasses adenocarcinoma, small cell carcinoma, and squamous cell carcinoma. Similarly, liver cancer consists of subtypes such as cholangiocarcinoma and hepatocellular carcinoma...

OBJECTIVE: The aim of this study was to determine whether a flipped classroom curriculum coupled with case-based learning would improve residents' perceptions of the learning environment, improve education outcomes, and increase faculty engagement. Research suggests that active learning yields better educational results compared with passive learning. However, faculty are more comfortable providing lectures that require only passive participation from learners. METHODS: A council was created to identify issues with the current format of the resident didactic curriculum and to redesign the neurosurgical curriculum and conference per Accreditation Council for Graduate Medical Education (ACGME) requirements...

OBJECTIVE: Machine learning (ML) is increasingly employed to diagnose medical conditions, with algorithms trained to assign a single label using a black-box approach. We created an ML approach using deep learning that generates outcomes that are transparent and in line with clinical, diagnostic rules. We demonstrate our approach for autism spectrum disorders (ASD), a neurodevelopmental condition with increasing prevalence. METHODS: We use unstructured data from the Centers for Disease Control and Prevention (CDC) surveillance records labeled by a CDC-trained clinician with ASD A1-3 and B1-4 criterion labels per sentence and with ASD cases labels per record using Diagnostic and Statistical Manual of Mental Disorders (DSM5) rules...

In this work we seek to enhance the frameworks practitioners in asset management and wealth management may adopt to asses how different screening rules may influence the diversification benefits of portfolios. The problem arises naturally in the area of Environmental, Social, and Governance (ESG) based investing practices as practitioners often need to select subsets of the total available assets based on some ESG screening rule. Once a screening rule is identified, one constructs a dynamic portfolio which is usually compared with another dynamic portfolio to check if it satisfies or outperforms the risk and return profile set by the company...