scholarly journals The Clinical Value of CT Scans for the Early Diagnosis and Treatment of Spinal Fractures and Paraplegia

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Peng Jia ◽  
Shan Zhu ◽  
Lin Guo
Keyword(s):  
Early Diagnosis ◽  
Clinical Diagnosis ◽  
Positive Impact ◽  
Spinal Fractures ◽  
Diagnosis And Treatment ◽  
Spinal Diseases ◽  
Clinical Value ◽  
Specificity And Sensitivity ◽  
Adjacent Structures

The early diagnosis and treatment of spinal fractures and paraplegia by CT scan is investigated in depth and its clinical value is discussed in this paper. In this paper, a novel circulatory generation adversarial network, Spine-GAN, is proposed for the diagnosis of various spinal diseases. The algorithmic model can fully automate the segmentation and classification of multiple spinal structures, such as intervertebral discs, vertebrae, and neuroforamina, simultaneously to intelligently generate a complete clinical diagnosis. The innovation of this method is that Spine-GAN not only overcomes the high variability and complexity of spinal structures in MRI images but also preserves the subtle differences between normal and abnormal spinal structures and dynamically learns obscure but important spatial pathological relationships between adjacent structures of the spine, thus overcoming the limitations of small datasets. Spine-GAN enables accurate segmentation, radiological classification, and pathological correlation representation of the three spinal diseases. Specifically, Spine-GAN achieves a pixel accuracy of 96.2% with a specificity and sensitivity distribution of 89.1% and 86%, respectively. The DMML-Net and Spine-GAN algorithm models have important applications and research values in the clinical diagnosis of spinal diseases and MRI image processing, as well as in the intelligent generation of medical image diagnostic reports, which are of great importance for the study of fine-grained image classification of pathological images. It also has a positive impact on the development of the software.

scholarly journals The significance of exosomes in the development and treatment of hepatocellular carcinoma

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Xin Li ◽  
Chuanyun Li ◽  
Liping Zhang ◽  
Min Wu ◽  
Ke Cao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Signal Transduction ◽  
Liver Cancer ◽  
Early Diagnosis ◽  
Cancer Cells ◽  
Clinical Diagnosis ◽  
Diagnosis And Treatment ◽  
Signal Transduction Pathways ◽  
Liver Cancer Cells ◽  
Different Types

AbstractHepatocellular carcinoma (HCC) is the most commonmalignancy. Exsome plays a significant role in the elucidation of signal transduction pathways between hepatoma cells, angiogenesis and early diagnosis of HCC. Exosomes are small vesicular structures that mediate interaction between different types of cells, and contain a variety of components (including DNA, RNA, and proteins). Numerous studies have shown that these substances in exosomes are involved in growth, metastasis and angiogenesis in liver cancer, and then inhibited the growth of liver cancer by blocking the signaling pathway of liver cancer cells. In addition, the exosomal substances could also be used as markers for screening early liver cancer. In this review, we summarized to reveal the significance of exosomes in the occurrence, development, diagnosis and treatment of HCC, which in turn might help us to further elucidate the mechanism of exosomes in HCC, and promote the use of exosomes in the clinical diagnosis and treatment of HCC.

Abstract 13031: Universal Screening for Familial Hypercholesterolemia in Young Adults: The Young FH Study

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Sachiko Okazaki ◽  
Satoru Takase ◽  
Masaki Tanaka ◽  
Midori Kubota ◽  
Eisuke Amiya ◽  
...  
Keyword(s):  
Young Adults ◽  
Early Diagnosis ◽  
Familial Hypercholesterolemia ◽  
Diagnostic Criteria ◽  
Clinical Diagnosis ◽  
Universal Screening ◽  
Diagnosis And Treatment ◽  
Cascade Screening ◽  
Increased Risk ◽  
The University

Introduction: Familial hypercholesterolemia (FH) is caused by genetic defects in low-density lipoprotein (LDL) receptor pathway, resulting in a persistent elevation of plasma LDL-cholesterol (LDL-C) levels as well as an increased risk of cardiovascular diseases. Early diagnosis and treatment are imperative for its management. Currently, FH patients are mainly identified by cascade screening. However, FH is underdiagnosed and undertreated, particularly in young adults, which warrants a systematic screening strategy. Hypothesis: Considering that the prevalence of FH is high (~0.4% in the general population) and that treatment of FH should be initiated earlier at the latest in young adults, we hypothesized that the universal screening of LDL-C in young adults is beneficial for early diagnosis and treatment of FH. Methods: At the University of Tokyo, plasma LDL-C levels have been measured at heath checkups for employees as well as new students. Young adults (18-30 years old) with hypercholesterolemia (LDL-C ≥ 160 mg/dL) identified by universal screening and referred to the University of Tokyo Hospital were eligible (the Young FH study). Those who have been identified by cascade screening were excluded. Mutation in FH-causing genes, as well as clinical and biochemical parameters useful for the clinical diagnosis of FH, were analyzed. The protocol was approved by the human genome, gene analysis research ethics committee of the University of Tokyo. Results: Of the total participants (n = 89, mean age 23.4 ± 3.4 years), 36 (40%) had mutations in LDLR or PCSK9 . The prevalence of mutation carriers was higher in non-obese than in obese participants (47% for body mass index (BMI) < 24 kg/m 2 vs. 26% for BMI ≥ 24). The sensitivity and specificity of clinical diagnosis were 28% and 85%, respectively, by Dutch Lipid Clinic Network Criteria (definite + probable FH), or 22% and 98%, respectively, by Japanese diagnostic criteria of FH. Conclusions: The universal screening of LDL-C effectively identifies FH high-risk patients in Japanese young adults. This screening may be beneficial in countries with low-prevalence of obesity or in non-obese populations. The use of clinical diagnostic criteria of FH for universal screening may lead to underdiagnosis.

scholarly journals Clinical value of CT in early diagnosis and treatment of acute abdomen

2013 ◽  
Vol 21 (32) ◽  
pp. 3520 ◽  
Author(s):  
Rong-Lin Zhai ◽  
Yue-Ping Long ◽  
Guo-Bin Wang
Keyword(s):  
Early Diagnosis ◽  
Acute Abdomen ◽  
Diagnosis And Treatment ◽  
Clinical Value

Application of Efficient Nanoparticles for Early Diagnosis and Treatment of Cancer

2015 ◽  
Vol 16 (8) ◽  
pp. 662-675 ◽  
Author(s):  
Athanasios Alexiou ◽  
Charalampos Vairaktarakis ◽  
Vasilis Tsiamis ◽  
Ghulam Ashraf
Keyword(s):  
Early Diagnosis ◽  
Diagnosis And Treatment

scholarly journals Small GTPases in Cancer: Still Signaling the Way

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1500
Author(s):  
Paulo Matos
Keyword(s):  
Early Diagnosis ◽  
Small Gtpases ◽  
Diagnosis And Treatment ◽  
The Way

In recent decades, many advances in the early diagnosis and treatment of cancer have been witnessed [...]

An effective technique for diabetic retinopathy using hybrid machine learning technique

2021 ◽  
pp. 096228022098354
Author(s):  
N Satyanarayana Murthy ◽  
B Arunadevi
Keyword(s):  
Diabetic Retinopathy ◽  
Short Term Memory ◽  
Early Recognition ◽  
Hybrid Techniques ◽  
Specificity And Sensitivity ◽  
Retinal Blood Vessels ◽  
Segmented Images ◽  
Fuzzy C Means Clustering ◽  
Working Region

Diabetic retinopathy (DR) stays as an eye issue that has continuously developed in individuals who experienced diabetes. The complexities in diabetes cause harm to the vein at the back of the retina. In outrageous cases, DR could swift apparition disaster or visual impairment. This genuine impact had the option to charge through convenient treatment and early recognition. As of late, this issue has been spreading quickly, particularly in the working region, which in the end constrained the interest of an analysis of this disease from the most prompt stage. Therefore, that are castoff to protect the progressions of this disorder, revealing of the retinal blood vessels (RBVs) play a foremost role. The growth of an abnormal vessel leads to the development steps of DR, where it can be well known by extracting the RBV. The recognition of the BV for DR by developing an automatic approach is a major aim of our research study. In the proposed method, there are two major steps: one is segmentation and the second one is classification of affected retinal BV. The proposed method uses the Kinetic Gas Molecule Optimization based on centroid initialization used for the Fuzzy C-means Clustering. In the classification step, those segmented images are given as input to hybrid techniques such as a convolution neural network with bidirectional-long short-term memory (CNN with Bi-LSTM). The learning degree of Bi-LSTM is revised by using the self-attention mechanism for refining the classification accuracy. The trial consequences disclosed that the mixture algorithm achieved higher accuracy, specificity, and sensitivity than existing techniques.

scholarly journals Preventing corneal blindness caused by keratitis using artificial intelligence

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhongwen Li ◽  
Jiewei Jiang ◽  
Kuan Chen ◽  
Qianqian Chen ◽  
Qinxiang Zheng ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Vision Loss ◽  
Learning System ◽  
Automated Classification ◽  
Slit Lamp ◽  
Resource Limited ◽  
The World ◽  
Different Types ◽  
Corneal Blindness

AbstractKeratitis is the main cause of corneal blindness worldwide. Most vision loss caused by keratitis can be avoidable via early detection and treatment. The diagnosis of keratitis often requires skilled ophthalmologists. However, the world is short of ophthalmologists, especially in resource-limited settings, making the early diagnosis of keratitis challenging. Here, we develop a deep learning system for the automated classification of keratitis, other cornea abnormalities, and normal cornea based on 6,567 slit-lamp images. Our system exhibits remarkable performance in cornea images captured by the different types of digital slit lamp cameras and a smartphone with the super macro mode (all AUCs>0.96). The comparable sensitivity and specificity in keratitis detection are observed between the system and experienced cornea specialists. Our system has the potential to be applied to both digital slit lamp cameras and smartphones to promote the early diagnosis and treatment of keratitis, preventing the corneal blindness caused by keratitis.

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