Decision Making Based on Fuzzy Aggregation Operators for Medical Diagnosis from Dental X-ray images.

Medical diagnosis is considered as an important step in dentistry treatment which assists clinicians to give their decision about diseases of a patient. It has been affirmed that the accuracy of medical diagnosis, which is much influenced by the clinicians' experience and knowledge, plays an important role to effective treatment therapies. In this paper, we propose a novel decision making method based on fuzzy aggregation operators for medical diagnosis from dental X-Ray images. It firstly divides a dental X-Ray image into some segments and identified equivalent diseases by a classification method called Affinity Propagation Clustering (APC+). Lastly, the most potential disease is found using fuzzy aggregation operators. The experimental validation on real dental datasets of Hanoi Medical University Hospital, Vietnam showed the superiority of the proposed method against the relevant ones in terms of accuracy.

The Combination of Adaptive Convolutional Neural Network and Bag of Visual Words in Automatic Diagnosis of Third Molar Complications on Dental X-Ray Images.

In dental diagnosis, recognizing tooth complications quickly from radiology (e.g., X-rays) takes highly experienced medical professionals. By using object detection models and algorithms, this work is much easier and needs less experienced medical practitioners to clear their doubts while diagnosing a medical case. In this paper, we propose a dental defect recognition model by the integration of Adaptive Convolution Neural Network and Bag of Visual Word (BoVW). In this model, BoVW is used to save the features extracted from images. After that, a designed Convolutional Neural Network (CNN) model is used to make quality prediction. To evaluate the proposed model, we collected a dataset of radiography images of 447 patients in Hanoi Medical Hospital, Vietnam, with third molar complications. The results of the model suggest accuracy of 84% ± 4%. This accuracy is comparable to that of experienced dentists and radiologists.

Preparation of cross-linked magnetic chitosan particles from steel slag and shrimp shells for removal of heavy metals.

In this study, a new method for preparation of cross-linked magnetic chitosan particles (MCPs) from steel slag and shrimp shells using green tea extract as crosslinking reagent has been presented. The MCPs obtained were characterized by means of X-ray diffraction analysis, Fourier-transform infrared spectroscopy, scanning electron microscopy and magnetic properties, and then were used to investigate the adsorption properties of Cu(II) and Ni(II) ions in aqueous solutions. The influence of experimental conditions such as contact time, pH value, adsorbent dose and initial metal concentration, and the possibility of regeneration were studied systematically. The Cu(II) and Ni(II) adsorption isotherms, kinetics and thermodynamics have been measured and discussed. The results show that the synthesized MCPs have high adsorption capacity for both metal ions (126.58 mg/g for Cu(II) and 66.23 mg/g for Ni(II)), and have excellent regeneration stability with efficiency of greater than 83% after five cycles of the adsorption-regeneration process. The adsorption process of Ni(II) and Cu(II) on MCPs was feasible, spontaneous and exothermic, and better described by the Langmuir model and pseudo-second-order kinetic equation. The MCPs can be applied as a low cost and highly efficient adsorbent for removal of heavy metals from wastewater due to its high adsorption capacity, easy recovery and good reusability.

Exposure assessment of chemical hazards in pork meat, liver, and kidney, and health impact implication in Hung Yen and Nghe An provinces, Vietnam.

OBJECTIVES: This study assesses the risk of exposure to hazardous chemical residues in pork meat, liver, and kidney collected at wet markets in Nghe An and Hung Yen provinces and discusses health impact implication. METHODS: 514 pig feed, kidney, liver, and pork samples were pooled and qualitatively and quantitatively analyzed for tetracyclines, fluoroquinolones, sulphonamide, chloramphenicol, ß-agonists, and heavy metals. We compare the results with current regulations on chemical residues and discuss health implications. RESULTS: Legal antibiotics were found in feed. Tetracycline and fluoroquinolones were not present in pork, but 11% samples were positive with sulfamethazine above maximum residue limits (MRL); 11% of packaged feed and 4% of pork pooled samples were positive for chloramphenicol, a banned substance; two feed, two liver, and one pork samples were positive for ß-agonists but did not exceed current MRL; 28% of pooled samples had lead, but all were below MRL; and all samples were negative for cadmium and arsenic. Thus, the health risks due to chemical hazards in pork in Hung Yen and Nghe An seemed not as serious as what were recently communicated to the public on the mass media. CONCLUSIONS: There is potential exposure to sulphonamide, chloramphenicol, and ß-agonists from pork. Risk communication needs to focus on banned chemicals, while informing the public about the minimal risks associated with heavy metals.

Integrating a project monitoring system into a public health network: experiences from Alive & Thrive Vietnam.

Little information is available about how to build a monitoring system to measure the output of preventive nutrition interventions, such as counselling on infant and young child feeding. This paper describes the Alive & Thrive Vietnam (A&T) project experience in nesting a large-scale project monitoring system into the existing public health information system (e.g. using the system and resources), and in using monitoring data to strengthen service delivery in 15 provinces with A&T franchises. From January 2012 to April 2014, the 780 A&T franchises provided 1,700,000 counselling contacts (~3/4 by commune franchises). In commune franchises in April 2014, 80% of mothers who were pregnant or with children under two years old had been to the counselling service at least one time, and 87% of clients had been to the service earlier. Monitoring data are used to track the progress of the project, make decisions, provide background for a costing study and advocate for the integration of nutrition counselling indicators into the health information system nationwide. With careful attention to the needs of stakeholders at multiple levels, clear data quality assurance measures and strategic feedback mechanisms, it is feasible to monitor the scale-up of nutrition programmes through the existing routine health information system.