ABSTRACT
Sentiment analysis is an emerging trend nowadays to understand people's sentiments in multiple situations in their quotidian life. Social media data would be utilized for the entire process ie the analysis and classification processes and it consists of text data and emoticons, emojis, etc. Many experiments were conducted in the antecedent studies utilizing Binary and Ternary Classification whereas Multi-class Classification gives more precise and precise Classification. In Multi-class Classification, the data would be divided into multiple sub-classes predicated on the polarities. Machine Learning and Deep Learning Techniques would be utilized for the classification process. Utilizing Social media, sentiment levels can be monitored or analysed. This paper shows a review of the sentiment analysis on Social media data for apprehensiveness or dejection detection utilizing various artificial intelligence techniques. In the survey, it was optically canvassed that social media data which consists of texts,emoticons and emojis were utilized for the sentiment identification utilizing various artificial intelligence techniques. Multi Class Classification with Deep Learning Algorithm shows higher precision value during the sentiment analysis.
ABSTRACT
BACKGROUND: Increasing incidence and significant stage migration from distant metastases to a localized disease, due to screening application of PSA, is taking place in carcinoma prostate. Also, role of radiotherapy is increasing in carcinoma prostate due to rapid strides in technology. AIM: The present retrospective study, evaluates escalating the dose in the treatment of localized carcinoma prostate using integration of multiple advanced techniques. SETTINGS AND DESIGN: The settings designed are: a) use of gold seed internal fiducial markers: b) clinical application of emerging Megavoltage Cone Beam Computed Tomography (MVCBCT) technology for Image Guided Radiotherapy (IGRT); c) Intensity Modulated Radiotherapy (IMRT); d) adopting biochemical method for follow-up. METHODS AND MATERIAL: Twelve consecutive, biopsy proven localized cancer of prostate patients, treated with dose escalation IMRT & IGRT protocol between August 2006 and January 2008, were analyzed. Gold seed markers in prostate were used for daily localization with MVCBCT or Electronic Portal Imaging (EPI). All patients underwent clinical and biochemical follow-up. STATISTICAL ANALYSIS & RESULTS: Planned dose of 7740 cGy was delivered in 10 out of 12 patients (83%). While one patient had migration of maximum of 3 mm, two others had 1 mm migration of one seed during course of treatment. One patient (8%) developed Grade II proctitis at 12th month. During the mean follow-up duration of 12.2 months, 92% (11/12) had biochemical control within 3 months of treatment. CONCLUSIONS: IGRT technique using MVCBCT for implanted fiducial gold seed localization was feasible for IMRT dose escalation in carcinoma prostate with excellent results.
Subject(s)
Carcinoma/radiotherapy , Prostatic Neoplasms/radiotherapy , Radiotherapy, Intensity-Modulated/methods , Radiotherapy/methods , Aged , Aged, 80 and over , Carcinoma/pathology , Humans , India , Male , Middle Aged , Neoplasm Staging , Prostatic Neoplasms/pathology , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted/methods , Retrospective Studies , Surgery, Computer-AssistedABSTRACT
The genetic map of Bremia lactucae was expanded utilizing 97 F(1) progeny derived from a cross between Finnish and Californian isolates (SF5xC82P24). Genetic maps were constructed for each parent utilizing 7 avirulence genes, 83 RFLP markers, and 347 AFLP markers, and a consensus map was constructed from the complete data set. The framework map for SF5 contained 24 linkage groups distributed over 835cM; the map for C82P24 contained 21 linkage groups distributed over 606cM. The consensus map contained 12 linkage groups with markers from both parents and 24 parent-specific groups. Six avirulence genes mapped to different linkage groups; four were located at the ends of linkage groups. The closest linkages between molecular markers and avirulence genes were 3cM to Avr4 and 1cM to Avr7. Mating type seemed to be determined by a single locus, where the heterozygote determined the B(2) type and the homozygous recessive genotype determined the B(1) type.
