Magnetocardiography-Based Ischemic Heart Disease Detection and Localization Using Machine Learning Methods.

OBJECTIVE: This study focused on developing a fast and accurate automatic ischemic heart disease detection/localization methodology. METHODS: T wave was segmented from averaged Magnetocardiography (MCG) recordings and 164 features were subsequently extracted. These features were categorized into three groups: time domain features, frequency domain features, and information theory features. Next, we compared different machine learning classifiers including: k-nearest neighbor, decision tree, support vector machine (SVM), and XGBoost. To identify ischemia heart disease (IHD) case, we selected three classifiers with best performance and applied model ensemble to average results. All 164 features were used in this stage. To localize ischemia, we classified IHD group according to stenosis locations, including left anterior descending (LAD), left circumflex artery (LCX), and right coronary artery (RCA). For this task, we used XGBoost classifier and 18 time domain features. RESULTS: For IHD detection, the SVM-XGBoost model achieved best results with accuracy = 94.03%, precision = 86.56%, recall = 97.78%, F-score = 92.79%, AUC = 0.98, and average precision = 0.98. For ischemia localization, XGBoost model achieved accuracy = 0.74, 0.68, and 0.65, for LAD, LCX, and RCA, respectively. CONCLUSION: we have developed an automatic IHD detection and localization system. We find that 1. T wave repolarization synchronicity is an important factor to distinguish IHD from normal subjects 2. Magnetic field pattern is associated with stenosis location. SIGNIFICANCE: The proposed machine learning method provides the clinicians a fast and accurate diagnosis tool to interpret MCG data, boosting its acceptance into clinics. Furthermore, the magnetic pole characteristics revealed by the method shows to be related to ischemia location, presenting the opportunity to noninvasively locate ischemia.

Clinical analysis of 19 cases of ectopic appendicitis with laparoscopic exploration and appendectomy / 国际外科学杂志

Objective To explore the clinical manifestations,diagnosed main points,laparoscopic trestment strategy of ectopic appendicitis.Methods The 19 clinical data of ectopic appendicitis,from April 2011 to April 2015 in our hosipital,were retrospective analysised,and we sum up the clinical manifestation,diagnosis and treatment,laparoscopic exploration indications and the technique of laparoscopic appendectomy.Laparoscopy exploration and laparoscopic appendectomy were made on all patients under general anesthesia by tracheal cannula.Results Of 19 patients,16 cases by ultrasonic examination get correct diagnosis before operation,of which the ultrasound diagnosis rate is 92.63％,3 limitations of acute peritonitis patients were preoperative misdiagno~s,they were the right kidney stones,acute cholecystitis and the right side of the annex inflammation;there were 2 patients converted to open operation,and the transfer rate is 10.53％.The blood loss of the operation is about 5-20 mL.They were ambulant after 9 hours,in full flow diet after 12 hours,and the average hospitalization time is 4 days.One patient,no other long-term complications were found postoperatively follow-up of 12 to 18 months,were poke holes in infection,and the complications of laparoscopic surgery is 5.27％.Conclusions Ectopic acute appendicitis has no specific clinical manifestation,and is easy to misdiagnosis.In the auxiliary examination,ultrasound is the first choice for the diagnosis of ectopic appendictis.Laparoscopy exploration and laparoscopic appendectomy are the ideal treatments of emergency treatment of ectopic appendicitis,and are worth of clinic application.