Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection

Semi-supervised object detection is crucial for 3D scene understanding, efficiently addressing the limitation of acquiring large-scale 3D bounding box annotations. Existing methods typically employ a teacher-student framework with pseudo-labeling to leverage unlabeled point clouds. However, producing reliable pseudo-labels in a diverse 3D space still remains challenging. In this work, we propose Diffusion-SS3D, a new perspective of enhancing the quality of pseudo-labels via the diffusion model for semi-supervised 3D object detection. Specifically, we include noises to produce corrupted 3D object size and class label distributions, and then utilize the diffusion model as a denoising process to obtain bounding box outputs. Moreover, we integrate the diffusion model into the teacher-student framework, so that the denoised bounding boxes can be used to improve pseudo-label generation, as well as the entire semi-supervised learning process. We conduct experiments on the ScanNet and SUN RGB-D benchmark datasets to demonstrate that our approach achieves state-of-the-art performance against existing methods. We also present extensive analysis to understand how our diffusion model design affects performance in semi-supervised learning.Comment: Accepted in NeurIPS 2023. Code is available at https://github.com/luluho1208/Diffusion-SS3

Performance evaluation on the implementation of Pre-established Medical Processes for nurse practitioners in the hospitals

In 2015, Taiwan announced the establishment of “Pre-established Medical Processes” and related regulations to assist nurse practitioners in the clinical tasks, maintain medical quality and patient safety, and provide protection in clinical practice. However, the effectiveness of implementation still needs to be improved and strengthened. This study adopts the TAM and the TTF as the research framework, and a cross-sectional design. The questionnaires are administered to the professional nurse practitioners in the hospitals of central Taiwan. A total of 300 questionnaires were distributed, and Smart PLS 3.0 and SPSS 24.0 were both applied to verify interpretability. The questionnaire recovery rate was 88.3%, and the overall predictive power was 65.2%. Technological characteristics and TTF had a significant impact on perceived usefulness

High ERCC1 expression predicts cisplatin-based chemotherapy resistance and poor outcome in unresectable squamous cell carcinoma of head and neck in a betel-chewing area

<p>Abstract</p> <p>Background</p> <p>This study was to evaluate the effect of excision repair cross-complementation group 1(ERCC1) expression on response to cisplatin-based induction chemotherapy (IC) followed by concurrent chemoradiation (CCRT) in locally advanced unresectable head and neck squamous cell carcinoma (HNSCC) patients.</p> <p>Methods</p> <p>Fifty-seven patients with locally advanced unresectable HNSCC who received cisplatin-based IC followed by CCRT from January 1, 2006 through January 1, 2008. Eligibility criteria included presence of biopsy-proven HNSCC without a prior history of chemotherapy or radiotherapy. Immunohistochemistry was used to assess ERCC1 expression in pretreatment biopsy specimens from paraffin blocks. Clinical parameters, including smoking, alcohol consumption and betel nuts chewing, were obtained from the medical records.</p> <p>Results</p> <p>The 12-month progression-free survival (PFS) and 2-year overall survival (OS) rates of fifty-seven patients were 61.1% and 61.0%, respectively. Among these patients, thirty-one patients had low ERCC1 expression and forty-one patients responded to IC followed by CCRT. Univariate analyses showed that patients with low expression of ERCC1 had a significantly higher 12-month PFS rates (73.3% vs. 42.3%, p < 0.001) and 2-year OS (74.2 vs. 44.4%, p = 0.023) rates. Multivariate analysis showed that for patients who did not chew betel nuts and had low expression of ERCC1 were independent predictors for prolonged survival.</p> <p>Conclusions</p> <p>Our study suggest that a high expression of ERCC1 predict a poor response and survival to cisplatin-based IC followed by CCRT in patients with locally advanced unresectable HNSCC in betel nut chewing area.</p

The Effectiveness of Traditional Chinese Medicine in Treating Patients with Leukemia

Leukemia is the most common malignancy among all childhood cancers and is associated with a low survival rate in adult patients. Since 1995, the National Health Insurance (NHI) program in Taiwan has been offering insurance coverage for Traditional Chinese Medicine (TCM), along with conventional Western medicine (WM). This study analyzes the status of TCM utilization in Taiwan, in both pediatric and adult patients with leukemia. A retrospective cohort study was conducted using population-based National Health Insurance Research Database of Registry of Catastrophic Illness, involving patient data from 2001 to 2010 and follow-up data through 2011. The effectiveness of TCM use was evaluated. Relevant sociodemographic data showed that both pediatric and adult patients who were TCM users one year prior to leukemia diagnosis were more likely to utilize TCM services for cancer therapy. A greater part of medical expenditure of TCM users was lower than that of TCM nonusers, except little discrepancy in drug fee of adult patients. The survival rate is also higher in TCM users. Altogether, these data show that TCM has the potential to serve as an adjuvant therapy when combined with conventional WM in the treatment of patients with leukemia

Self-supervised learning-based general laboratory progress pretrained model for cardiovascular event detection

The inherent nature of patient data poses several challenges. Prevalent cases amass substantial longitudinal data owing to their patient volume and consistent follow-ups, however, longitudinal laboratory data are renowned for their irregularity, temporality, absenteeism, and sparsity; In contrast, recruitment for rare or specific cases is often constrained due to their limited patient size and episodic observations. This study employed self-supervised learning (SSL) to pretrain a generalized laboratory progress (GLP) model that captures the overall progression of six common laboratory markers in prevalent cardiovascular cases, with the intention of transferring this knowledge to aid in the detection of specific cardiovascular event. GLP implemented a two-stage training approach, leveraging the information embedded within interpolated data and amplify the performance of SSL. After GLP pretraining, it is transferred for TVR detection. The proposed two-stage training improved the performance of pure SSL, and the transferability of GLP exhibited distinctiveness. After GLP processing, the classification exhibited a notable enhancement, with averaged accuracy rising from 0.63 to 0.90. All evaluated metrics demonstrated substantial superiority (p < 0.01) compared to prior GLP processing. Our study effectively engages in translational engineering by transferring patient progression of cardiovascular laboratory parameters from one patient group to another, transcending the limitations of data availability. The transferability of disease progression optimized the strategies of examinations and treatments, and improves patient prognosis while using commonly available laboratory parameters. The potential for expanding this approach to encompass other diseases holds great promise.Comment: published in IEEE Journal of Translational Engineering in Health & Medicin

Identifying Chinese Herbal Medicine Network for Endometriosis: Implications from a Population-Based Database in Taiwan

Background. Endometriosis is a common but bothersome gynecological disease, and Chinese herbal medicine (CHM) is used for treating endometriosis. The aim of this study is to explore CHM network and core treatments for endometriosis by analyzing nationwide CHM prescription database. Methods. From 1998 to 2013, the CHM prescriptions made primarily for endometriosis among women diagnosed with endometriosis (ICD-9-CM code: 671) by gynecologists during their reproductive age were collected. CHM network analysis was then carried out by using association rule mining and social network analysis. Results. A total of 12,986 CHM prescriptions made for endometriosis were analyzed. There were 556 kinds of CHM ever used, and, in average, each prescription was composed of 6.2 CHMs. Gui-Zhi-Fu-Ling-Wan (GZFLW) was used most frequently, followed by Cyperus rotundus (28.1% and 18.8% of all prescriptions, resp.). Additionally, the combination of Cyperus rotundus with GZFLW (8.0%) was the most frequently used combination of two CHMs. CHM network showed that GZFLW was the core CHM for endometriosis and graphically demonstrated the extensive coverage of TCM syndromes and pathogenesis of endometriosis. Conclusions. CHM network provides graphical demonstration and summary of commonly used CHMs for endometriosis, and further studies are warranted based on these findings

Bioequivalence Evaluation of Two Formulations of Celecoxib 200 mg Capsules in Healthy volunteers by using a validated LC/MS/MS method

The bioequivalence study to compare a new formulation of celecoxib to its reference formulation was designed as an open-label, randomized, single-dose, two-way crossover, comparative bioavailability study by using a validated LC/MS/MS method. In order to determine the plasma concentrations of celecoxib, a sensitive LC/MS/MS method was developed. The method was validated to possess adequate specificity, linearity, precision, accuracy and stability. The linearity of calibration curve was assessed between the concentration intervals (5–2000 ng/mL) with a correlation coefficient over 0.999. Regarding pharmacokinetic investigation, the mean celecoxib AUC0-t values from the test and reference drug formulations were 7360.44 ± 1714.14 h•ng/mL and 7267.48 ± 2077.68 h•ng/mL, respectively, and the corresponding AUC0-∞ values were 8197.45 ± 2040.31 h•ng/mL and 7905.54 ± 2286.12 h•ng/mL, respectively. The Cmax of the test and reference drugs was 705.30 ± 290.63 ng/mL and 703.86 ± 329.91 ng/mL, respectively, and the corresponding Tmax was 3.4 ± 1.6 h and 2.9 ± 1.4 h. Lastly, the T1/2 values of the test and reference drugs were 13.9 ± 7.9 h and 12.9 ± 7.7 h, respectively. The 90% confidence intervals for AUC0-t, AUC0-∞, and Cmax were 97.00-108.85, 98.01-112.09, and 93.20-116.13, respectively, satisfying the bioequivalence criteria of 80-125% range. In conclusion, these results demonstrated that the bioequivalence of two formulations of celecoxib was established successfully by utilizing present developed LC/MS/MS method

Atomic-scale magnetic doping of monolayer stanene by revealing Kondo effect from self-assembled Fe spin entities

Atomic-scale spin entity in a two-dimensional topological insulator lays the foundation to manufacture magnetic topological materials with single atomic thickness. Here, we have successfully fabricated Fe monomer, dimer and trimer doped in the monolayer stanene/Cu(111) through a low-temperature growth and systematically investigated Kondo effect by combining scanning tunneling microscopy/spectroscopy (STM/STS) with density functional theory (DFT) and numerical renormalization group (NRG) method. Given high spatial and energy resolution, tunneling conductance (dI/dU) spectra have resolved zero-bias Kondo resonance and resultant magnetic-field-dependent Zeeman splitting, yielding an effective spin Seff = 3/2 with an easy-plane magnetic anisotropy on the self-assembled Fe atomic dopants. Reduced Kondo temperature along with attenuated Kondo intensity from Fe monomer to trimer have been further identified as a manifestation of Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction between Sn-separated Fe atoms. Such magnetic Fe atom assembly in turn constitutes important cornerstones for tailoring topological band structures and developing magnetic phase transition in the single-atom-layer stanene