Medical data mining in sentiment analysis based on optimized swarm search feature selection.

In this paper, we propose a novel technique termed as optimized swarm search-based feature selection (OS-FS), which is a swarm-type of searching function that selects an ideal subset of features for enhanced classification accuracy. In terms of gaining insights from unstructured medical based texts, sentiment prediction is becoming an increasingly crucial machine learning technique. In fact, due to its robustness and accuracy, it recently gained popularity in the medical industries. Medical text mining is well known as a fundamental data analytic for sentiment prediction. To form a high-dimensional sparse matrix, a popular preprocessing step in text mining is employed to transform medical text strings to word vectors. However, such a sparse matrix poses problems to the induction of accurate sentiment prediction model. The swarm search in our proposed OS-FS can be optimized by a new feature evaluation technique called clustering-by-coefficient-of-variation. In order to find a subset of features from all the original features from the sparse matrix, this type of feature selection has been a commonly utilized dimensionality reduction technique, and has the capability to improve accuracy of the prediction model. We implement this method based on a case scenario where 279 medical articles related to 'meaningful use functionalities on health care quality, safety, and efficiency' from a systematic review of previous medical IT literature. For this medical text mining, a multi-class of sentiments, positive, mixed-positive, neutral and negative is recognized from the document contents. Our experimental results demonstrate the superiority of OS-FS over traditional feature selection methods in literature.

Cerebral activation effects of acupuncture at Yanglinquan(GB34) point acquired using resting-state fMRI.

OBJECTIVE: To explore the central mechanism of acupuncture points for regional homogeneity(ReHo) of resting state in brain function after acupuncture at GB34. METHODS: Ten healthy volunteers were enrolled, which included 4 males and 6 females, aged 20-34 years old with median age of 23. The GE Signa HDxt 3.0 T magnetic resonance imaging were performed before (control group) and after acupuncture at GB34, and differences of different brain ReHo of 2 groups by statistical parametric mapping (SPM8) software and ReHo data processing methods were analyzed. The statistically different brain regions were obtained by false discovery rate corrected (FDR-Corrected). RESULTS: Compared with control group, the anterior cingulated gyrus, left temporal gyrus, right inferior parietal lobule, right frontal gyrus were enhanced ReHo after acupuncture at GB34. The left thalamus, right insular cortex, left inferior frontal gyrus, right anterior cingulate were decreased ReHo after acupuncture at GB34. CONCLUSION: It is demonstrated that the signal synchronization change ReHo in different brain regions including cognitive, motor, default network, limbic system and other parts of encephalic region after acupuncture at GB34, suggesting that the central mechanism of acupuncture at GB34 is the result of all levels of the combined effects of brain networks.

Application of magnetic resonance imaging in diagnosis of Uterus Cervical Carcinoma.

BACKGROUND AND OBJECTIVE: Effective treatment of Uterus Cervical Carcinoma (UCC) rely heavily on the precise pre-surgical staging. The conventional International Federation of Gynecology and Obstetrics (FIGO) system based on clinical examination is being applied worldwide for UCC staging. Yet its performance just appears passable. Thus, this study aims to investigate the value of applying Magnetic Resonance Imaging (MRI) with clinical examination in staging of UCC. MATERIALS AND METHODS: A retrospective dataset involving 164 patients diagnosed with UCC was enrolled in this study. The mean age of this study population was 46.1 years (range, 28-#x2013;75 years). All patients underwent operations and UCC types were confirmed by pathological examinations. The tumor stages were determined by two experienced Gynecologist independently based on FIGO examinations and MRI. The diagnostic results were also compared with the post-operative pathologic reports. Statistical data analysis on diagnostic performance was then done and reported. RESULTS: The study results showed that the overall accuracy of applying MRI in UCC staging was 82.32%, while using FIGO staging method, the staging accuracy was 59.15%. CONCLUSIONS: MRI is suitable to evaluate tumor extent with high accuracy, and it can offer more objective information for the diagnosis and staging of UCC. Compared with clinical examinations based on FIGO, MRI illustrated relatively high accuracy in evaluating UCC staging, and is worthwhile to be recommended in future clinical practice.

WITHDRAWN: Sentiment prediction by text mining medical documents using optimized swarm search-based feature selection.

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Cerebral activation effects of acupuncture using Zusanli (ST36) and Yanglingquan (GB34) points based on Regional Homogeneity indices: A resting-state fMRI study.

OBJECTIVE: This study aimed to observe the cerebral activation effects of acupuncturing the Zusanli (ST36) plusYanglingquan (GB34) points in young healthy volunteers based on Regional Homogeneity (ReHo) indices. METHODS: Ten healthy volunteers were enrolled, including 4 males and 6 females between the ages 20 and 34 years with a median age of 23 years. Magnetic resonance imaging (GE Signa HDxt 3.0T) was performed in four groups: Before acupuncture (Control Group), after acupuncture at Zusanli (ST36 Group), after acupuncture at Yanglingquan (GB34 Group) and after acupuncture at both Zusanli and Yanglingquan (Compatibility Group). Differences in the brain ReHo indices of the 4 groups were analyzed by statistical parametric mapping (SPM8) and ReHo data processing methods. The significantly different brain regions were obtained using a false discovery rate correction (FDR-Corrected). RESULTS: The ReHo indices revealed that the main significant effect was in the Compatibility Group. Compared with the resting state of the Control Group, the ReHo values of the Compatibility Group increased in the right middle frontal gyrus (BA8, 9), left superior temporal areas (BA22), ventral anterior cingulate area (BA24) and right inferior parietal lobe (BA40); in contrast, the ReHo values decreased in the left thalamus, right insular cortex (BA13), left inferior frontal lobe (BA9) and right dorsal anterior cingulate area (BA32). Our analysis showed that the Compatibility Group had higher ReHo values than the left inferior parietal lobule (BA40) and right frontal cortex (BA6) of the ST36 Group and the posterior lobe of the right cerebellum, dorsal anterior cingulate (BA32), left and right middle frontal gyrus (BA46, BA9), left precuneus (BA7), right inferior parietal love (BA40) of the GB34 Group. CONCLUSION: The results of our neuroimaging study suggest that the combination of acupoints could more widely activate areas of the brain compared to a single acupoint. Additionally, the combination of acupoints can activate some new brain areas and generate new curative effects.