Delineation of high resolution climate regions over the Korean Peninsula using machine learning approaches

In this research, climate classification maps over the Korean Peninsula at 1 km resolution were generated using the satellite-based climatic variables of monthly temperature and precipitation based on machine learning approaches. Random forest (RF), artificial neural networks (ANN), k-nearest neighbor (KNN), logistic regression (LR), and support vector machines (SVM) were used to develop models. Training and validation of these models were conducted using in-situ observations from the Korea Meteorological Administration (KMA) from 2001 to 2016. The rule of the traditional Koppen-Geiger (K-G) climate classification was used to classify climate regions. The input variables were land surface temperature (LST) of the Moderate Resolution Imaging Spectroradiometer (MODIS), monthly precipitation data from the Tropical Rainfall Measuring Mission (TRMM) 3B43 product, and the Digital Elevation Map (DEM) from the Shuttle Radar Topography Mission (SRTM). The overall accuracy (OA) based on validation data from 2001 to 2016 for all models was high over 95%. DEM and minimum winter temperature were two distinct variables over the study area with particularly high relative importance. ANN produced more realistic spatial distribution of the classified climates despite having a slightly lower OA than the others. The accuracy of the models using high altitudinal in-situ data of the Mountain Meteorology Observation System (MMOS) was also assessed. Although the data length of the MMOS data was relatively short (2013 to 2017), it proved that the snowy, dry and cold winter and cool summer class (Dwc) is widely located in the eastern coastal region of South Korea. Temporal shifting of climate was examined through a comparison of climate maps produced by period: from 1950 to 2000, from 1983 to 2000, and from 2001 to 2013. A shrinking trend of snow classes (D) over the Korean Peninsula was clearly observed from the ANN-based climate classification results. Shifting trends of climate with the decrease/increase of snow (D)/temperate (C) classes were clearly shown in the maps produced using the proposed approaches, consistent with the results from the reanalysis data of the Climatic Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC)

Misdiagnosis in occupational and environmental medicine: a scoping review

Introduction There has been no comprehensive review for misdiagnosis in Occupational and Environmental Medicine (OEM). The possible ramifications of an occupational disease (OD) or an environmental disease (ED) misdiagnosis are not just confined to the individual case but may extend to others exposed to the occupational or environmental hazard. Therefore, a comprehensive scoping review of published literature is imperative for understanding the nature of misdiagnoses in OEM. Methods A medical librarian searched MEDLINE (PubMed), EMBASE, and the Cochrane Library (on 06 November 2020). All collected OEM misdiagnoses were classified based on 2 conceptual frameworks, the typical framework, and the causation model. The distribution of misdiagnosis across each medical specialty, each diagnostic step of the typical framework and the causation model, and false-negative and false-positive were summarized. Results A total of 79 articles were included in the scoping review. For clinical specialty, pulmonology (30 articles) and dermatology or allergy (13 articles) was most frequent and second-most frequent, respectively. For each disease, occupational and environmental interstitial lung diseases, misdiagnosed as sarcoidosis (8 articles), and other lung diseases (8 articles) were most frequent. For the typical framework, the most vulnerable step was the first step, evidence of a disease (38 articles). For the causation model, the first step, knowledge base, was the most vulnerable step (42 articles). For reported articles, the frequency of false-negative (55 articles) outnumbered the frequency of false-positive (15 articles). Discussion In OEM, compared to general medicine, causal misdiagnosis associated with the probability of causation is also important. For making a diagnosis in OEM, a knowledge base about possible ODs and EDs is essential. Because of this reason, the education and training of treating physicians for common ODs and EDs are important. For ODs and EDs, various intentional behaviors of stakeholders should be considered. This scoping review might contribute to the improvement of understanding for misdiagnosis in OEM.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector

A Dual-Prompting for Interpretable Mental Health Language Models

Despite the increasing demand for AI-based mental health monitoring tools, their practical utility for clinicians is limited by the lack of interpretability.The CLPsych 2024 Shared Task (Chim et al., 2024) aims to enhance the interpretability of Large Language Models (LLMs), particularly in mental health analysis, by providing evidence of suicidality through linguistic content. We propose a dual-prompting approach: (i) Knowledge-aware evidence extraction by leveraging the expert identity and a suicide dictionary with a mental health-specific LLM; and (ii) Evidence summarization by employing an LLM-based consistency evaluator. Comprehensive experiments demonstrate the effectiveness of combining domain-specific information, revealing performance improvements and the approach's potential to aid clinicians in assessing mental state progression

Classification and mapping of paddy rice by combining Landsat and SAR time series data

Rice is an important food resource, and the demand for rice has increased as population has expanded. Therefore, accurate paddy rice classification and monitoring are necessary to identify and forecast rice production. Satellite data have been often used to produce paddy rice maps with more frequent update cycle (e.g., every year) than field surveys. Many satellite data, including both optical and SAR sensor data (e.g., Landsat, MODIS, and ALOS PALSAR), have been employed to classify paddy rice. In the present study, time series data from Landsat, RADARSAT-1, and ALOS PALSAR satellite sensors were synergistically used to classify paddy rice through machine learning approaches over two different climate regions (sites A and B). Six schemes considering the composition of various combinations of input data by sensor and collection date were evaluated. Scheme 6 that fused optical and SAR sensor time series data at the decision level yielded the highest accuracy (98.67% for site A and 93.87% for site B). Performance of paddy rice classification was better in site A than site B, which consists of heterogeneous land cover and has low data availability due to a high cloud cover rate. This study also proposed Paddy Rice Mapping Index (PMI) considering spectral and phenological characteristics of paddy rice. PMI represented well the spatial distribution of paddy rice in both regions. Google Earth Engine was adopted to produce paddy rice maps over larger areas using the proposed PMI-based approach

Emphysematous Gastritis Associated with Invasive Gastric Mucormycosis: A Case Report

Emphysematous gastritis is a rare form of phlegmonous gastritis, characterized by air in the wall of the stomach due to invasion by gas-forming microorganisms. The most commonly involved microorganisms are streptococci, Escherichia coli, Pseudomonas aeruginosa, Clostrodium perfrigens and Staphylococcus aureus. Gastrointestinal mucormycosis is another rare condition, which is most frequently occurs in the stomach. Because emphysematous gastritis associated with invasive gastric mucormycosis is an extremely rare clinical condition and both are life-threatening diseases, early precise diagnosis and early treatment should be done to avoid mortality. Herein we present an extremely rare case of emphysematous gastritis associated with invasive gastric mucormycosis. A 43-yr-old man, suffering from alcoholism and diabetes, has experienced diffuse abdominal pain for 4 days. Abdominal computed tomography scan demonstrated gas within the stomach wall. A histologic examination of the total gastrectomy specimen showed several gas-filled bubbles in the wall, along with numerous fungal hyphae throughout the necrotic stomach wall. He died of multiorgan failure secondary to disseminated mucormycosis, despite the intensive medical therapy

Primary Polymorphous Low-Grade Adenocarcinoma of Lung Treated by Sleeve Bronchial Resection : A Case Report

We report a surgical case of primary polymorphous low-grade adenocarcinoma (PLGA) of the minor salivary gland-type of the lung. A PLGA originating from the right upper lobar bronchial inlet was successfully treated by sleeve right upper lobectomy. PLGAs are thought to be indolent tumors that are preferentially localized to the palate, and they affect the minor salivary glands almost exclusively. Until now, two cases of distant metastases to the lung have been reported in the English literature. To the best of our knowledge, only one case of PLGA of minor salivary gland-type of the lung without evidence of a previous oropharyngeal primary tumor has been reported in the English literature. But the case was not a single lesion; it was bilateral tumors accompanied by tumors of the cervical lymph nodes. We report here the first case of a single primary PLGA of the minor salivary gland-type of the lung, which was successfully treated by sleeve bronchial resection of right upper lobe

Evaluation of an international faculty development program for developing countries in Asia: the Seoul Intensive Course for Medical Educators

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Abstract Background The issue of collaboration in medical education is becoming prominent. Some faculty development programs have suggested an approach for promoting collaboration on a global level. However, non-English-speaking developing countries in Asia, especially in Southeast Asia, do not take advantage of them due to their unique context, such as language and culture. To address these issues, Seoul National University College of Medicine initiated a 6-week international faculty development program called the Seoul Intensive Course for Medical Educators for 16 fellows from five Asian countries (Cambodia, Laos, Mongolia, Myanmar, and Vietnam). The aim of this study is to report the evaluation results of the outcome of the program and discuss better ways of collaborating with developing countries. Methods Three levels of collaboration—intraorganizational, intranational, and international—were central initiatives of the program. Prior to setting up the program details, we first established four design principles, following which the contents, materials, and facilitators were determined to maintain consistency with the design principles. The evaluation of the program was done with Kirkpatricks four-level model. Most of the evaluation data for level 1 were collected by two questionnaires, the post-module survey and the post-program survey. Portfolios and progress reports were mainly used to collect outcome data for levels 2 and 3, respectively. Results The reaction was generally positive throughout the program and there was a significant correlation between satisfaction and relevance to ones job or needs. Despite the fellows propensity for overestimating themselves, both the evaluators and fellows reported that there was significant improvement in learning. Opinions on the impact or urgency of the topics were slightly different from country to country; however, the answers regarding feasibility were fairly similar. Moreover, we could observe from the post-program progress reports that the transfer of learning was actively in progress, mainly for topics that were highly feasible. Conclusions These results show that the program was successful in terms of its effectiveness. Consistent and timely support is essential for the sustainable development of the medical education systems in these countries. Further understanding of the underlying factors on transfer (level 3) could improve the effectiveness of faculty development programs for developing countries

Spatial and temporal variabilities of spring Asian dust events and their impacts on chlorophyll-a concentrations in the western North Pacific Ocean

Author Posting. © American Geophysical Union, 2017. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 44 (2017): 1474–1482, doi:10.1002/2016GL072124.As the western North Pacific Ocean is located downwind of the source regions for spring Asian dust, it is an ideal location for determining the response of open waters to these events. Spatial analysis of spring Asian dust events from source regions to the western North Pacific, using long-term daily aerosol index data, revealed three different transport pathways supported by the westerly wind system: one passing across the northern East/Japan Sea (40°N–50°N), a second moving over the entire East/Japan Sea (35°N–55°N), and a third flowing predominantly over the Siberian continent (>50°N). Our results indicate that strong spring Asian dust events can increase ocean primary productivity by more than 70% (>2-fold increase in chlorophyll-a concentrations) compared to weak/nondust conditions. Therefore, attention should be paid to the recent downturn in the number of spring Asian dust events and to the response of primary production in the western North Pacific to this change.Korean government (MSIP) Grant Numbers: 2015R1C1A1A01052051, NRF-C1ABA001-2011-0021064; Korea Polar Research Institute (KOPRI) Grant Number: PE17030; NOAA Grant Number: NA11OAR4310063; WHOI2017-08-1

Immunohistochemical Analysis of Non-Small Cell Lung Cancer: Correlation with Clinical Parameters and Prognosis

Non-small cell lung cancers (NSCLC) vary in their biologic behavior. Recurrence and tumor-related mortality may be attributable to molecular abnormalities in primary tumors. This study evaluated such immunophenotypes with regard to cell cycle regulation and proliferation, apoptosis, and angiogenesis, to determine their significance for patient outcome. Core biopsies from 219 patients with NSCLC were assembled on tissue microarrays, and the expressions of p16, p21, p27, cyclin B1, cyclin E, Ki-67, caspase-3, survivin, bcl-2, VEGF, and endostatin were evaluated by immunohistochemistry. Despite previously described prognostic relevance of some of the investigated molecules, many of those markers were not directly associated with recurrence or survival. However, there was a trend for p16 immunoreactivity to be associated with a good prognosis (57% vs. 42% in 5-yr survival) (p=0.071). bcl-2 expression was strongly correlated with a better outcome (65% vs. 45% in 5-yr survival) (p=0.029), and the hazard of death for bcl-2 positive patients was 0.42 times of that for bcl-2 negative patients (p=0.047). A multivariate analysis with Cox proportional hazards model confirmed that the lymph node status (p=0.043) and stage (p=0.003) were other independent prognostic factors. Our results suggest that p16 and bcl-2 provide prognostic information independent of the TNM stage in NSCLC