Social networking and dental care: State of the art and analysis of the impact on dentists, dental practices and their patients

Health Social networking sites offering search, reviews and recommendation are gaining popularity. This paper reviews the most popular social networking sites related to dental care. Social networks such as DrOogle and Yelp enable their users to review and rate their dentists and dental practices. Such information is then used to rank and recommend dentists or dental practices to new users/patients. This paper compares the dental care social networking sites in terms of their features and criteria supported for search, reviews and recommendations of dentists or dental practices. Mismatches between features and criteria among different dental care reviews sites are identified, which may cause inconsistency in the recommendations in the dental care. Therefore, this paper proposes a new framework for dynamic dental care recommendation system which takes both local (personalised) and global (crowdsourced) trust into account. It analyses the impact of current social networks on dentists, dental practices and their patients. Finally, it identifies the open issues and challenges that need to be addressed to design a trustworthy recommendation system for both the dental professionals and their patients

Analysing and using subjective criteria to improve dental care recommendation systems

Online reviews and rating sites are shaping industries as the users rely on recommendations given by former consumers and sharing opinions on the web. Dentistry has also been impacted by dental patients' reviews. This paper classifies trust-related information for dental care recommendations onto 4 categories: context, relationship, reputation and subjective criteria. It discusses each category and describes how they help focussing on trust when matching patients and dentists in brief. The paper then focuses on subjective criteria and presents the results of a survey aimed at showing trustrelated information emerged from subjective characteristics. Traits of personalities are used as subjective characteristics of patients and that of dentists are derived from the online patients' reviews. 580 Australian patients were surveyed to determine what factors affect their decision to find the trusted dentist. Subjective characteristics of dentists such as dentists' qualities and experienced dentists are considered the most important factors after location and cost. The most preferred dentists' qualities by almost all types of personalities are experienced, professional and quality of service. When the patients are further classified based on levels of fear, their preferences for dentists' qualities changed. Subjective qualities of both patients and dentists are important factors to improve the matching capability for the dental care recommendation systems

Improving dental care recommendation systems using trust and social networks

The growing popularity of Health Social Networking sites has a tremendous impact on people's health related experiences. However, without any quality filtering, there could be a detrimental effect on the users' health. Trust-based techniques have been identified as effective methods to filter the information for recommendation systems. This research focuses on dental care related social networks and recommendation systems. Trust is critical when choosing a dental care provider due to the invasive nature of the treatment. Surprisingly, current dental care recommendation systems do not use trust-based techniques, and most of them are simple reviews and ratings sites. This research aims at improving dental care recommendation systems by proposing a new framework, taking trust into account. It derives trust from both users' social networks and from existing crowdsourced information on dental care. Such a framework could be used for other healthcare recommendation systems where trust is of major importance. © 2014 IEEE

Improving the matching process of dental care recommendation systems by using subjective criteria for both patients and dentists

Nowadays, healthcare recommendation systems are matching health professionals with patients based on preferences such as location, type of treatments, price, availability or other information including their type of health insurance. In the health social network domain, subjective criteria such as attitude, personality and behaviour have not been considered for matching of patients and health professionals. In this research, we focus on dental care recommendation systems and we aim at introducing subjective criteria in the matching process. Patients are profiled in terms of attitudes, personalities and behaviours through a set of questionnaires, derived from the popular methods such as DISC (Dominant, Influencer, Steady, and Compliant) personality test. In addition, we use crowdsourcing to extract feedback from patients and to profile dentists according to their qualities (e.g.: Friendly, caring, rude, etc.). These qualities are then used in the matching process. A thorough investigation on how to improve the matching process of a patient's subjective profile with a dentist's qualities is done through online questionnaires and focus group. The research aims at deriving a dynamic set of matching rules to improve the process of recommendation that includes subjective aspects so that in the future, patients can be better matched with the 'right' dentist for them

Structure and Applications of Gold in Nanoporous Form

Nanoporous gold (np-Au) has many interesting and useful properties that make it a material of interest for use in many technological applications. Its biocompatible nature and ability to serve as a support for self-assembled monolayers of alkanethiols and their derivative make it a suitable support for the immobilization of carbohydrates, enzymes, proteins, and DNA. Its chemically inert, physically robust and conductive high-surface area makes it useful for the design of electrochemistry-based chemical/bio-sensors and reactors. Furthermore, it is also used as solid support for organic molecular synthesis and biomolecules separation. Its enhanced optical property has application in design of plasmonics-based sensitive biosensors. In fact, np-Au is one of the few materials that can be used as a transducer for both optical and electrochemical biosensing. Due to the presence of low-coordination surface sites, np-Au shows remarkable catalytic activity for oxidation of molecules like carbon monoxide and methanol. Owing to the importance of np-Au, in this chapter we will highlight different strategies of fabrication of np-Au and its emerging applications based on its unique properties

SharpRazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images

Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional gradients, and multiple filters for hair of varying widths. We develop an alternate entropy-based processing adaptive thresholding method. White or light-colored hair, and ruler marks are detected separately and added to the final hair mask. A classifier removes noise objects. Finally, a new technique of inpainting is presented, and this is utilized to remove the detected object from the lesion image. Results: The proposed algorithm is tested on two datasets, and compares with seven existing methods measuring accuracy, precision, recall, dice, and Jaccard scores. SharpRazor is shown to outperform existing methods. Conclusion: The Shaprazor techniques show the promise to reach the purpose of removing and inpaint both dark and white hair in a wide variety of lesions

Chimeranet: U-Net for Hair Detection in Dermoscopic Skin Lesion Images

Hair and ruler mark structures in dermoscopic images are an obstacle preventing accurate image segmentation and detection of critical network features. Recognition and removal of hairs from images can be challenging, especially for hairs that are thin, overlapping, faded, or of similar color as skin or overlaid on a textured lesion. This paper proposes a novel deep learning (DL) technique to detect hair and ruler marks in skin lesion images. Our proposed ChimeraNet is an encoder-decoder architecture that employs pretrained EfficientNet in the encoder and squeeze-and-excitation residual (SERes) structures in the decoder. We applied this approach at multiple image sizes and evaluated it using the publicly available HAM10000 (ISIC2018 Task 3) skin lesion dataset. Our test results show that the largest image size (448 x 448) gave the highest accuracy of 98.23 and Jaccard index of 0.65 on the HAM10000 (ISIC 2018 Task 3) skin lesion dataset, exhibiting better performance than for two well-known deep learning approaches, U-Net and ResUNet-a. We found the Dice loss function to give the best results for all measures. Further evaluated on 25 additional test images, the technique yields state-of-the-art accuracy compared to 8 previously reported classical techniques. We conclude that the proposed ChimeraNet architecture may enable improved detection of fine image structures. Further application of DL techniques to detect dermoscopy structures is warranted

Who pays and who benefits? How different models of shared responsibilities between formal and informal carers influence projections of costs of dementia management

<p>Abstract</p> <p>Background</p> <p>The few studies that have attempted to estimate the future cost of caring for people with dementia in Australia are typically based on total prevalence and the cost per patient over the average duration of illness. However, costs associated with dementia care also vary according to the length of the disease, severity of symptoms and type of care provided. This study aimed to determine more accurately the future costs of dementia management by taking these factors into consideration.</p> <p>Methods</p> <p>The current study estimated the prevalence of dementia in Australia (2010-2040). Data from a variety of sources was recalculated to distribute this prevalence according to the location (home/institution), care requirements (informal/formal), and dementia severity. The cost of care was attributed to redistributed prevalences and used in prediction of future costs of dementia.</p> <p>Results</p> <p>Our computer modeling indicates that the ratio between the prevalence of people with mild/moderate/severe dementia will change over the three decades from 2010 to 2040 from 50/30/20 to 44/32/24.</p> <p>Taking into account the severity of symptoms, location of care and cost of care per hour, the current study estimates that the informal cost of care in 2010 is AU$3.2 billion and formal care at AU$5.0 billion per annum. By 2040 informal care is estimated to cost AU$11.6 billion and formal care$AU16.7 billion per annum. Interventions to slow disease progression will result in relative savings of 5% (AU$1.5 billion) per annum and interventions to delay disease onset will result in relative savings of 14$4 billion) of the cost per annum.</p> <p>With no intervention, the projected combined annual cost of formal and informal care for a person with dementia in 2040 will be around AU$38,000 (in 2010 dollars). An intervention to delay progression by 2 years will see this reduced to AU$35,000.</p> <p>Conclusions</p> <p>These findings highlight the need to account for more than total prevalence when estimating the costs of dementia care. While the absolute values of cost of care estimates are subject to the validity and reliability of currently available data, dynamic systems modeling allows for future trends to be estimated.</p

Magnetic Texture in Insulating Single Crystal High Entropy Oxide Spinel Films

Magnetic insulators are important materials for a range of next generation memory and spintronic applications. Structural constraints in this class of devices generally require a clean heterointerface that allows effective magnetic coupling between the insulating layer and the conducting layer. However, there are relatively few examples of magnetic insulators which can be synthesized with surface qualities that would allow these smooth interfaces and precisely tuned interfacial magnetic exchange coupling which might be applicable at room temperature. In this work, we demonstrate an example of how the configurational complexity in the magnetic insulator layer can be used to realize these properties. The entropy-assisted synthesis is used to create single crystal (Mg0.2Ni0.2Fe0.2Co0.2Cu0.2)Fe2O4 films on substrates spanning a range of strain states. These films show smooth surfaces, high resistivity, and strong magnetic responses at room temperature. Local and global magnetic measurements further demonstrate how strain can be used to manipulate magnetic texture and anisotropy. These findings provide insight into how precise magnetic responses can be designed using compositionally complex materials that may find application in next generation magnetic devices

Factors associated with the utilisation of postnatal care services among the mothers of Nepal: analysis of Nepal Demographic and Health Survey 2011

Background: Postnatal care is essential to save the life of the mother and newborn. Knowledge on the determinants of postnatal care assists the policy makers to design, justify and implement appropriate interventions. The current study aimed to analyse the factors associated with utilisation of postnatal care services by mothers in Nepal based on the data from Nepal Demographic and Health Survey (NDHS) 2011. Methods: This study utilised the data from NDHS 2011. The association between utilisation of at least one postnatal care visit (within 6 weeks of delivery) and immediate postnatal care (within 24 hours of delivery) with selected factors was examined by using Chi-square test (?2), followed by multiple logistic regression.Result: Of the 4079 mothers, 43.2% reported attending postnatal care within the first six weeks of birth, while 40.9% reported attending immediate postnatal care. Mothers who were from urban areas, from rich families, who were educated, whose partners were educated, who delivered in a health facility, who had attended a four or more antenatal visits, and whose delivery was attended by a skilled attendant were more likely to report attending at least one postnatal care visit. On the other hand, mothers who reported agricultural occupation, and whose partners performed agricultural occupation were less likely to have attended at least one postnatal care visit. Similarly, mothers who were from the urban areas, from rich families, who were educated, whose partners were educated, who had attended four or more antenatal visits, who delivered in a health facility and had delivered in the presence of a skilled birth attendant were more likely to report attending immediate postnatal care. Mothers who reported agricultural occupation, and whose partners performed agricultural occupation were less likely to attend immediate postnatal care. Conclusion: The majority of postnatal mothers in Nepal did not seek postnatal care. Increasing utilisation of the recommended four or more antenatal visits, delivery at health facility and increasing awareness and access to services through community-based programs especially for the rural, poor, and less educated mothers may increase postnatal care attendance in Nepal