Miracle-dz/UniFAR-FTUs huggingface dataset:
A surgical hospitalist system in Korea: a preliminary study of the effects on hospital costs and postoperative outcomes

Purpose The aim of this study is to investigate the effect of the surgical hospitalist system on postoperative outcomes and hospital costs for surgical patients. Methods We reviewed the medical records of 522 patients who were admitted to the divisions of colorectal and gastrointestinal surgery for operation from September to December 2017 at Severance Hospital, Yonsei University College of Medicine in Seoul, Korea. All patients were divided into 2 groups; one that was managed by surgical hospitalists group (HG) and another that was managed by non-hospitalist residents group (NHG) after elective surgery. Postoperative outcomes and hospital costs were analyzed for each group. Results Two hundred ninety-eight patients were managed by HG and 189 patients were managed by NHG after surgery. The length of hospital stay in the first group was shorter (9.6 ± 5.8 days vs. 12.2 ± 7.9 days, P < 0.001), the incidence of complications was lower (44.6% vs. 55.6%, P = 0.019), and the readmission rate was lower (3.0% vs. 6.9%, P = 0.046) in the HG than in the NHG. The difference in total hospital costs was not significant between the HG and the NHG (₩8,381,304 vs. ₩9,242,493, P = 0.559), but surgery-independent hospital costs were lower in the HG than in the NHG (₩3,020,873 vs. ₩3,923,308, P = 0.001). Conclusion The surgical hospitalist system reduced the length of hospital stay, the incidence of postoperative complications, and the readmission rates of surgical patients. This led to the effect of a reduction in total hospital costs.
Predicting Mental Health Problems with Automatic Identification of Metaphors

Mental health problems are prevalent and an important issue in medicine. However, clinical diagnosis of mental health problems is costly, time-consuming, and often significantly delayed, which highlights the need for novel methods to identify them. Previous psycholinguistic and psychiatry research has suggested that the use of metaphors in texts is linked to the mental health status of the authors. In this paper, we propose a method for automatically detecting metaphors in texts to predict various mental health problems, specifically anxiety, depression, inferiority, sensitivity, social phobias, and obsession. We perform experiments on a composition dataset collected from second-language students and on the eRisk2017 dataset collected from Social Media. The experimental results show that our approach can help predict mental health problems in authors of written texts, and our algorithm performs better than other state-of-the-art methods. In addition, we report that the use of metaphors even in nonnative languages can be indicative of various mental health problems.
Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition

Breast cancer becomes the second major cause of death among women cancer patients worldwide. Based on research conducted in 2019, there are approximately 250,000 women across the United States diagnosed with invasive breast cancer each year. The prevention of breast cancer remains a challenge in the current world as the growth of breast cancer cells is a multistep process that involves multiple cell types. Early diagnosis and detection of breast cancer are among the greatest approaches to preventing cancer from spreading and increasing the survival rate. For more accurate and fast detection of breast cancer disease, automatic diagnostic methods are applied to conduct the breast cancer diagnosis. This paper proposed the fuzzy-ID3 (FID3) algorithm, a fuzzy decision tree as the classification method in breast cancer detection. This study aims to resolve the limitation of an existing method, ID3 algorithm that unable to classify the continuous-valued data and increase the classification accuracy of the decision tree. FID3 algorithm combined the fuzzy system and decision tree techniques with ID3 algorithm as the decision tree learning. FUZZYDBD method, an automatic fuzzy database definition method, would be used to design the fuzzy database for fuzzification of data in the FID3 algorithm. It was used to generate a predefined fuzzy database before the generation of the fuzzy rule base. The fuzzified dataset was applied in FID3 algorithm, which is the fuzzy version of the ID3 algorithm. The inference system of FID3 algorithm is simple with direct extraction of rules from generated tree to determine the classes for the new input instances. This study also analysed the results using three breast cancer datasets: WBCD (Original), WDBC (Diagnostic) and Coimbra. Furthermore, the comparison of FID3 algorithm with the existing methods is conducted to verify the proposed method’s capability and performance. This study identified that the combination of FID3 algorithm with FUZZYDBD method is reliable, robust and managed to perform well in breast cancer classification.
Solidification path of the AlFeMnSi alloys in a stage of primary intermetallic phases precipitation

In this work, an analysis of the solidification course of the AlFeMnSi alloys was carried out in the Al alloys of Fe, Mn, and Si concentrations in a range supplementary for those examined until now. The morphology of the pre-dendrite and pre-eutectic precipitates of the AlFeMnSi intermetallics has been revealed in relation to alloy composition. The phase attribution of the AlFeMnSi intermetallics forming primary pre-dendrite and pre-eutectic crystals was revealed in situ through local diffraction methods. The results obtained in the present work, as compared with data published previously, revealed the critical limit of the Mn concentration, necessary to stabilize the αc-AlFeMnSi phase as equal ≤ 0.5 wt. %, in the alloys AlFe≤3.0MnSi6 and AlFe≤1.5MnSi11 and ≥ 0.5 wt. % in AlFe≥3.0MnSi11.
A Recurrent Temporal Model for Semantic Levels Categorization Based on Human Visual System

Humans can categorize an object in different semantic levels. For example, a dog can be categorized as an animal (superordinate), a terrestrial animal (basic), or a dog (subordinate). Recent studies have shown that the duration of stimulus presentation can affect the mechanism of categorization in the brain. Rapid stimulus presentation will not allow top-down influences to be applied on the visual cortex, whereas in the nonrapid, top-down influences can be established and the final result will be different. In this paper, a spiking recurrent temporal model based on the human visual system for semantic levels of categorization is introduced. We showed that the categorization problem for up-right and inverted images can be solved without taking advantage of feedback, but for the occlusion and deletion problems, top-down feedback is necessary. The proposed computational model has three feedback paths that express the effects of expectation and the perceptual task, and it is described by the type of problem that the model seeks to solve and the level of categorization. Depending on the semantic level of the asked question, the model changes its neuronal structure and connections. Another application of recursive paths is solving the expectation effect problem, that is, compensating the reduce in firing rate by the top-down influences due to the available features in the object. In addition, in this paper, a psychophysical experiment is performed and top-down influences are investigated through this experiment. In this experiment, by top-down influences, the speed and accuracy of the categorization of the subjects increased for all three categorization levels. In both the presence and absence of top-down influences, the remarkable point is the superordinate advantage.
A Study Protocol to Explore and Improve Access to Medical Services and Information for Recently Diagnosed Elderly Patients with Cancer in Rural Settings

Introduction: This two-phase study seeks to contribute to research in the field of rural cancer health; specifically, the aim is to gain insight into the experiences of seeking, accessing and using information and health services throughout the cancer journey (diagnosis, treatment and follow-up care) for recently diagnosed (≤6 months) older patients (≥65 years) in rural areas. Methods and analysis: Data will be collected through in-depth semi-structured interviews. In phase 1 (before 23rd March 2020) interviews were conducted with healthcare professionals (HCP) to explore their experiences of delivering care to their elderly patients. In the second phase (starting January 2021) we will conduct interviews with cancer patients to understand the impact of COVID-19 and shielding on their experiences of being diagnosed, attending appointments and accessing and receiving support from community organisations and informal support from family and friends. Data gathered will be analysed using the Framework Method. Ethics: The study has been approved by the Health Research Authority and the United Lincolnshire Hospitals NHS Trust. Initial favourable ethical opinion was granted on 1st October 2019. Second favourable ethical opinion for amendments to reflect the impact of COVID-19 was received on 10th August 2020. The study protocol has been registered on Research Registry.
Do gene-environment interactions play a role in COVID-19 distribution? The case of Alpha-1 Antitrypsin, air pollution and COVID-19

Background Gene-environment interactions are relevant for several respiratory diseases. This communication raises the hypothesis that the severity of COVID-19, a complex disease where the individual response to the infection may play a significant role, could partly result from a gene-environment interaction between air-pollution and Alpha-1 Antitrypsin (AAT) genes. Methods To evaluate the impact of the AAT and air pollution interaction on COVID-19, we introduced an AAT*air pollution global risk score summing together, in each country, an air pollution score (ozone, nitrogen dioxide and fine particulate matter) and an AAT score (which sums the ranked frequency of MZ, SZ, MS). We compared this global score with the ranking of European countries in terms of death number per million persons. Results The ranking of the AAT*air pollution global risk score matched the ranking of the countries in terms of the observed COVID-19 deaths per 1M inhabitants, namely in the case of the first European countries: Belgium, UK, Spain, Italy, Sweden, France. We observed parallelism between the number of COVID deaths and the AAT*air pollution global risk in Europe. AAT anti-protease, immune-modulating and coagulation-modulating activities may explain this finding, although very speculatively. Conclusions Even if further studies taking into account genetic background, population density, temporal dynamics of individual epidemics, access to healthcare, social disparities and immunological response to SARS-CoV2 are needed, our preliminary observation urges to open a discussion on gene-environment interactions in COVID-19.
Xiao Chai Hu Tang for Peptic Ulcers: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

A peptic ulcer (PU) is a digestive disorder most commonly found in clinical practice. An oriental herbal formula, Xiao Chai Hu Tang (XCHT), has been used to treat PU for an extended period in China. The effectiveness and safety of XCHT in treating peptic ulcers was evaluated using a systematic review of randomized controlled trials (RCTs). Studies were systematically retrieved from CNKI, Embase, Medline, PubMed, SinoMed, VIP, Wanfang, and Web of Science. The following information was extracted from the relevant RCTs: the clinical efficacy rate, recurrence rate, clinical efficacy of traditional Chinese medicine, and the adverse effects. 13 RCTs, including 1334 patients, were included in this review. The meta-analysis showed that treatment with XCHT was superior to conventional pharmacotherapy (CPT) in improving the clinical efficacy rate (RR: 1.20, 95% confidence intervals (CIs): 1.08–1.34, P=0.0007), poor appetite (RR: 0.30, 95% CI: 0.15–0.61, P=0.0009), abdominal distension (RR: 0.61, 95% CI: 0.39–0.96, P=0.03), vomiting (RR: 0.33, 95% CI: 0.19–0.55, P < 0.0001), and stomach pain (RR: 0.36, 95% CI: 0.19–0.68, P=0.002) and reducing adverse events (RR: 0.23, 95% CI: 0.07–0.69, P=0.009). XCHT considerably increased the total clinical efficacy rate (RR: 1.22, 95% CI: 1.15–1.30, P < 0.00001) as both monotherapy and adjunctive therapy. The recurrence rate (RR = 0.29; 95% CI: 0.16–0.52, P < 0.0001) was remarkably decreased in the XCHT plus CPT group. The meta-analysis did not show a significant beneficial effect of XCHT compared with CPT in reducing the recurrence rate (RR = 0.45; 95% CI: 0.07–3.10, P=0.42) and acid reflux (RR: 0.76, 95% CI: 0.47–1.23, P=0.26). Our findings show that XCHT can treat peptic ulcers as part of an alternative medicine approach.
Whole mitochondrial genome analysis in Chinese patients with keratoconus

Purpose Keratoconus (KC) is a corneal disorder characterized by corneal ectasia, progressive corneal thinning, and conical protrusion. This study aimed to elucidate the mitochondrial gene profile in Chinese patients with KC, analyze the mitochondrial haplogroup and heteroplasmy, and further explore the association between mitochondrial genes and KC. Methods Mitochondrial sequencing was conducted on 100 patients with KC and 100 matched controls. Haplogroup analysis was conducted with logistic regression analysis. The heteroplasmy was analyzed with ANOVA (ANOVA) and Student t test. Sequence kernel association tests (SKATs) were performed to analyze the association between mitochondrial genes and KC. Mtoolbox, Mitoclass.1, and APOGEE were used to estimate the impact of the identified variants in protein-coding genes. PON-mt-tRNA was used to annotate the impact of the variants in tRNA. RNAstructure was used to predict the secondary structures of native and mutated tRNAs. Results We identified 689 variants in patients with KC and 725 variants in controls (with 308 variants shared by both). The mitochondrial haplogroups exhibited no statistically significant differences between the two groups. Based on the heteroplasmy analysis, the number of heteroplasmic variants in the complete mitochondrial genome, RNA coding regions, and noncoding regions were statistically significantly different in the KC cases and controls (p<0.05). The heteroplasmic levels of the m. 16180_16182delAA, m.16182insC, and m.14569 G>C variants in the KC cases were statistically significantly higher than those in the controls (p<0.05). The SKAT analysis showed that the COX3 and TRNH genes were statistically significantly associated with KC (p<0.05). Among the nine variants of COX3 included in the SKAT analysis (m.9300G>A, m.9316T>C, m.9327A>G, m.9355A>G, m.9468A>G, m.9612G>A, m.9804G>A, m.9957G>A, and m.9966 G>A), m.9612G>A was predicted to be deleterious by Mtoolbox. The m.9316T>C, m.9327A>G, m.9355A>G, m.9612G>A, m.9804G>A, and m.9957G>A variants were predicted to be damaging by Mitoclass.1. The m.9355A>G and m.9804G>A variants were predicted to be pathogenic by APOGEE. All identified variants located in TRNH (m.12153C>T, m.12178C>T, and m.12192G>A) were predicted to be neutral by the PON-mt-tRNA website. Conclusions This study presents the mitochondrial gene profile of Chinese patients with KC and demonstrated that the COX3 and TRNH genes were associated with KC.
Risk of Non-Alcoholic Fatty Liver Disease in Xanthelasma Palpebrarum

Background Xanthelasma palpebrarum (XP) is a sign of hyperlipidemia and is closely linked to atherosclerosis. Since fatty liver shares similar risk factors with atherosclerosis, we hypothesized that patients with XP are also at risk of non-alcoholic fatty liver disease (NAFLD). Methods In this retrospective cohort study, 37 patients with XP were compared with sex- and age-matched controls undergoing general health examination. Moreover, demographic information and lipid profiles were compared. The risk of NAFLD was evaluated using the hepatic steatosis and ZJU indices. In addition, we analyzed publicly available RNA sequencing data from the GSE48452 and GSE61260 datasets in the Gene Expression Omnibus database. Findings Patients with XP had higher scores of hepatic steatosis index (37 ± 1.13 vs 32 ± 0.82, p=0.0006) and ZJU index (38.77 ± 1.0 vs 33.88 ± 0.74, p=0.0002). In addition, they had higher levels of lipid parameters, including total cholesterol, low-density lipoprotein (LDL), and fasting glucose. Among patients with fatty liver, individuals presenting with XP showed higher serum levels of total cholesterol (216 ± 10.4 vs 188.9 ± 7.6, p=0.04), fasting glucose (117.1 ± 6.4 vs 98.3 ± 2.4, p=0.002), and low-density lipoprotein (145.1 ± 8.7 vs 115.6 ± 6.4, p=0.009) than those without XP. In gene expression analysis, individuals presenting with non-alcoholic steatohepatitis showed higher Z scores of xanthelasma than those without non-alcoholic steatohepatitis. Conclusion Our results suggest that individuals with XP have a higher risk of progression to NAFLD and develop a more severe dyslipidemia.
An effective classification framework for brain-computer interface system design based on combining of fNIRS and EEG signals

Background The brain-computer interface (BCI) is a relatively new but highly promising special field that is actively used in basic neuroscience. BCI includes interfaces for human-computer communication based directly on neural activity concerning mental processes. Fundamental BCI components consist of different units. In the first stage, the EEG and NIRS signals obtained from the individuals are preprocessed, and the signals are brought to a certain standard. Methods In order to realize proposed framework, a dataset containing Motor Imaginary and Mental Activity tasks are prepared with Electroencephalography (EEG) and Near-Infrared Spectroscopy (NIRS) signal. First of all, HbO and HbR curves are obtained from NIRS signals. Hbo, HbR, HbO+HbR, EEG, EEG+HbO and EEG+HbR features tables are created with the features obtained by using HbO, HbR, and EEG signals, and feature weighted is carried out with the k-Means clustering centers based attribute weighting method (KMCC-based) and the k-Means clustering centers difference based attribute weighting method (KMCCD-based). Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and k-Nearest Neighbors algorithm (kNN) classifiers are used to see the classifier differences in the study. Results As a result of this study, an accuracy rate of 99.7% (with kNN classifier and KMCCD-based weighting) is obtained in the data set of Motor Imaginary. Similarly, an accuracy rate of 99.9% (with SVM and kNN classifier and KMCCD-based weighting) is obtained in the Mental Activity dataset. The weighting method is used to increase the classification accuracy, and it has been shown that it will contribute to the classification of EEG and NIRS BCI systems. The results show that the proposed method increases classifiers’ performance, offering less processing power and ease of application. In the future, studies could be carried out by combining the k-Means clustering center-based weighted hybrid BCI method with deep learning architectures. Further improved classifier performances can be achieved by combining both systems.
A Novel Non-Invasive Device for the Assessment of Central Venous Pressure in Hospital, Office and Home

Background Venous congestion can be quantified by central venous pressure (CVP) and its monitoring is crucial to understand and follow the hemodynamic status of patients with cardio-respiratory diseases. The standard technique for CVP measurement is invasive, requiring the insertion of a catheter into a jugular vein, with potential complications. On the other hand, the current non-invasive methods, mainly based on ultrasounds, remain operator-dependent and are unsuitable for use in the home environment. In this paper, we will introduce a novel, non-invasive device for the hospital, office and home assessment of CVP. Methods After describing the measurement concept, we will report a preliminary experimental study enrolling 5 voluntary healthy subjects to evaluate the VenCoM measurements’ repeatability, and the system’s capability in measuring small elicited venous pressure variations (2 mmHg), as well as an induced venous hypertension within a pathological range (12÷20 mmHg). Results The experimental measurements showed a repeatability of ±1mmHg. The VenCoM device was able to reliably detect the elicited venous pressure variations and the simulated congestive status. Discussion and Conclusion The proposed non-invasive VenCoM device is able to provide a fast and repeatable CVP estimate, having a wide spectrum of potential clinical applications, including the monitoring of venous congestion in heart failure patients and in subjects with renal and hepatic dysfunction, as well as pulmonary hypertension (PH) that can be extended to pneumonia COVID-19 patients even after recovery. The device needs to be tested further on a large sample size of both healthy and pathological subjects, to systematically validate its reliability and impact in clinical setting.
Clinical Effectiveness of Various Surgical Procedures Addressing Long Head of Biceps Pathology: Protocol for a Systematic Review and Meta-Analysis

Introduction: The long head of biceps tendon is a common source of anterior shoulder pain and impaired function. Multiple surgical procedures are available as treatment options, but the optimal procedure is not known. The aim of this systematic review and meta-analysis is to review the literature to assess the clinical effectiveness of various surgical procedures to treat pain arising from the long head of biceps. Methods: The study protocol was designed and registered prospectively on PROSPERO (International prospective register for systematic reviews). Electronic databases used for the literature search will include MEDLINE, EMBASE, PsycINFO, and The Cochrane Library. Randomised controlled trials (RCTs) evaluating surgical procedures on the long head of biceps will be included. Our primary outcome is any functional patient-reported outcome measure related to the shoulder. Secondary outcomes will include the rate of ‘Popeye’ deformity, the rate of biceps cramping pain, the rate of complications, objective measurements of strength testing such as dynamometer, and other patient-reported outcome measures not specific to the shoulder such as the Visual-Analog Scale (VAS) for pain. Methodological quality of included studies will be assessed using The Cochrane Risk of Bias Tool 2.0 and the Jadad score. Inconsistency and bias across included studies will be assessed statistically. Comparable outcome data will be pooled and analysed quantitatively or qualitatively as appropriate. Ethics and dissemination: No ethical clearances required for this study. We plan to publish this systematic review and meta-analysis in a peer-reviewed journal. It will also be presented at various national and international conferences. Highlights Evaluating the clinical effectiveness of surgical procedures for long head of biceps pathology. Randomised controlled trials. Biceps tenodesis and biceps tenotomy. Systematic review compliant with the PRISMA guideline.