The Application of Deep Learning in the Risk Grading of Skin Tumors for Patients Using Clinical Images.

According to diagnostic criteria, skin tumors can be divided into three categories: benign, low degree and high degree malignancy. For high degree malignant skin tumors, if not detected in time, they can do serious harm to patients' health. However, in clinical practice, identifying malignant degree requires biopsy and pathological examination which is time costly. Furthermore, in many areas, due to the severe shortage of dermatologists, it's inconvenient for patients to go to hospital for examination. Therefore, an easy to access screening method of malignant skin tumors is needed urgently. Firstly, we spend 5 years to build a dataset which includes 4,500 images of 10 kinds of skin tumors. All instances are verified pathologically thus trustworthy; Secondly, we label each instance to be either low-risk, high-risk or dangerous in which Junctional nevus, Intradermal nevus, Dermatofibroma, Lipoma and Seborrheic keratosis are low-risk, Basal cell carcinoma, Bowen's disease and Actinic keratosis are high-risk, Squamous cell carcinoma and Malignant melanoma are dangerous; Thirdly, we apply the Xception architecture to build the risk degree classifier. The area under the curve (AUC) for three risk degrees reach 0.959, 0.919 and 0.947 respectively. To further evaluate the validity of the proposed risk degree classifier, we conduct a competition with 20 professional dermatologists. The results showed the proposed classifier outperforms dermatologists. Our system is helpful to patients in preliminary screening. It can identify the patients who are at risk and alert them to go to hospital for further examination.

Surgical Myectomy and Myotomy for Refractory Blepharospasm in Meige Syndrome Patients: A Case Report.

Meige syndrome is a rare neurological disease characterized by segmental dystonia, specifically blepharospasm and oromandibular dystonia. These symptoms are often accompanied by complex movements of the eyelids, lower facial muscles, mandible, and neck muscles. Bilateral blepharospasm is the most common feature of this disease. In this case report, we present the successful treatment of refractory blepharospasm in a 72-year-old woman with Meige syndrome via 2 incisions resulting from myectomy and in situ surgery.

Clinical patterns and characteristics of uveitis in a secondary hospital in southern China.

AIM: To investigate the characteristics of uveitis in a secondary hospital in southern China. METHODS: We reviewed all records of patients with uveitis at Hengli Hospital from January 2008 to December 2011. Demographic data, past history, ophthalmic examinations and other laboratory tests were analyzed. RESULTS: One hundred and ninety-nine uveitis patients were enrolled in this study, including 134 (67.3%) males and 65 females (32.7%) with an average age of 41.0±15.1y. The anatomical distribution included 103 (51.8%) cases of anterior uveitis, followed by panuveitis (65, 32.7%), posterior uveitis (29, 14.6%) and intermediate uveitis (2, 1.0%). Of the 98 (49.2%) non-idiopathic cases, there were 10.1% Behcet's disease, 9.5% Vogt-Koyanagi-Harada (VKH) syndrome, 7.5%infectious uveitis, 7.5% traumatic uveitis and 3.5% postoperative uveitis. CONCLUSION: Idiopathic anterior and posterior uveitis, Behcet's disease, VKH syndrome, infectious uveitis and traumatic uveitis are the most common uveitis entities in a secondary hospital in southern China. Additional measures should be taken to prevent infectious and traumatic uveitis.