hmp-munet-hybrid-deep-learning-framework-for-automated-skin-lesion

HMP-MUNet: A Hybrid Deep Learning Framework for Automated Skin Lesion Segmentation in Dermoscopic Images

Computer-aided diagnosis systems for cutaneous lesions face significant challenges in achieving both high diagnostic accuracy and computational ...

liaoning university

 Conclusions of previous cohort studies on the relationship between 25-hydroxyvitamin D level and the risk of dementia and Alzheimer's disease were not consistent. Thus, we performed a dose-response meta-analysis to evaluate this relationship by summarizing cohort studies.  Pubmed, Embase, Cochrane, and Web of Science databases were searched for relevant studies. Cohort studies concerning the association between 25-hydroxyvitamin D level and dementia or Alzheimer's disease were included. Results of studies were pooled and the dose-response relationship was determined using a random-effect model.  Ten cohort studies, with 28,640 participants were included. A significant inverse relationship was found between 25-hydroxyvitamin D level and the risk of dementia and Alzheimer's disease. In addition, we found a linear dose-response relationship in that a 10 nmol/L increase in 25-hydroxyvitamin D level may lead to a 5% decrease in the risk of dementia (relative risk, 0.95; 95% confidence interval, 0.93-0.98) and 7% in the risk of Alzheimer's disease (relative risk, 0.93; 95% confidence interval, 0.89-0.97).  Plasma or serum 25-hydroxyvitamin D concentration was inversely related to the risk of dementia and Alzheimer's disease, consistent with a linear dose-response relationship.

25-Hydroxyvitamin D Levels and the Risk of Dementia and Alzheimer's Disease: A Dose-Response Meta-Analysis.

In the process of treating pro-diseases with acupuncture, traditional Chinese medicine (TCM) doctors may fine-tune acupuncture prescriptions according to different prior experiences. Different prescriptions will affect the efficiency and effect of acupuncture treatment, and even excessive acupoint selection may cause psychological pressure on patients. We still lack an effective means to analyze the meridian system and acupoint specificity to clarify the mapping relationship between acupoints and diseases. Given the inability of modern medical technology to provide effective evidence support for meridians and acupoints, we combined acupuncture theory with network science for an interdisciplinary discussion. In this paper, we constructed a weighted undirected acupoint-disease network (ADN) based on clinical acupuncture prescription literature and proposed a high-specificity key node mining method based on ADN. Combined with the principle of acupoint selection in TCM, the proposed method balanced the contribution of local areas to the network based on the distribution characteristics of meridians and selected 30 key acupoints with high influence on the global topology according to the evaluation index of key nodes. Finally, we compared the proposed method with the other six classical node importance evaluation algorithms in terms of resolution, network loss, and accuracy. The comprehensive results show that the marked key acupoint nodes make outstanding contributions to the connectivity, topological structure, and weighted benefits of the network, and the stability and specificity of the algorithm guarantee the reliability of the key acupoint nodes. We consider that these key acupoints with high centrality in ADN can be used as core acupoints to help researchers explore targeted and high-impact acupoint combinations under resource constraints and optimize existing acupuncture prescriptions.

A Key Node Mining Method Based on Acupoint-Disease Network (ADN): A New Perspective for Exploring Acupoint Specificity.

Tubular structure segmentation in chest CT images can reduce false positives (FPs) dramatically and improve the performance of nodules malignancy levels classification.

A robust and efficient framework for tubular structure segmentation in chest CT images.

The relationship between serum uric acid and risk of stroke is still controversial. Therefore, we conducted a meta-analysis based on the cohort study to explore the relationship between serum uric acid and risk of stroke, and further illuminate whether there is a linear or non-linear relationship between them. We manually searched the database including Cochrane, PubMed, Embase, Web of Science, and selected cohort studies focusing on the relationship between serum uric acid and stroke risk. Random effect model was used for statistical analysis. Twenty-one cohort studies involving 818,098 participants were included. The pooled relative risk for the high-vs-low categories was 1.22 (95% CI: 1.15-1.30). In addition, there was a non-linear dose-response relationship between uric acid and stroke risk. Serum uric acid was in the range of 3-5 mg/dl, with the lowest risk of stroke. In conclusion, high serum uric acid level increases the risk of stroke, with a non-linear dose-response relationship.

Serum uric acid and risk of stroke: a dose-response meta-analysis.

Terahertz (THz) wave has demonstrated a good prospect in recent years, but the resolution is still one of the problems that restrict the application of THz technology in medical imaging. Paraffin-embedded samples are mostly used in THz medical imaging studies, which are thicker and significantly different from the current gold standard slice pathological examination in sample preparation. In addition, THz absorption in different layers of normal and cancerous tissues also remains to be further explored. In this study, we constructed a high-resolution THz imaging system to scan non-tumorous adjacent tissue slices and gastric cancer (GC) tissue slices. In this system, a THz quantum cascade laser emitted a pulsed 3 THz signal and the transmitted THz wave was received by a THz detector implemented in a 65 nm CMOS process. The slice thickness was only 20 μm, which was close to that of the medical pathology examination. We successfully found THz transmittance differences between different layers of normal gastric tissues based on THz images, and the resolution could reach 60 μm for the first time. The results indicated that submucosa had a lower THz transmittance than that of mucosa and muscular layer in non-tumorous adjacent tissue. However, in GC tissue, THz transmittance of mucosa and submucosa was similar, caused by the decreased transmittance of mucosa, where the cancer occurs. Therefore, we suppose that the similar terahertz transmittance between gastric mucosa and submucosa may indicate the appearance of cancerization. The images obtained from our THz imaging system were clearer than those observed with naked eyes, and can be directly compared with microscopic images. This is the first application of THz imaging technology to identify non-tumorous adjacent tissue and GC tissue based on the difference in THz wave absorption between different layers in the tissue. Our present work not only demonstrated the potential of THz imaging to promote early diagnosis of GC, but also suggested a new direction for the identification of normal and cancerous tissues by analyzing differences in THz transmittance between different layers of tissue.

Article	Year
25-Hydroxyvitamin D Levels and the Risk of Dementia and Alzheimer's Disease: A Dose-Response Meta-Analysis. Frontiers in aging neuroscience\| PubMed ID: 30473663	2018
A Key Node Mining Method Based on Acupoint-Disease Network (ADN): A New Perspective for Exploring Acupoint Specificity. Evidence-based complementary and alternative medicine : eCAM\| PubMed ID: 32765631	2020
A robust and efficient framework for tubular structure segmentation in chest CT images. Technology and health care : official journal of the European Society for Engineering and Medicine\| PubMed ID: 33427700	2021
Serum uric acid and risk of stroke: a dose-response meta-analysis. Journal of clinical biochemistry and nutrition\| PubMed ID: 34025024	2021
Early detection of gastric cancer high-resolution terahertz imaging system. Frontiers in bioengineering and biotechnology\| PubMed ID: 36588946	2022

Han Shi

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