Journal of Health & Medical Informatics

Personal diet management is key to fighting the obesity epidemic. Recent advances in smartphones and wearable sensor technologies have empowered automated food monitoring through food image processing and eating episode detection, with the goal to conquer drawbacks of traditional food journaling that is labour intensive, inaccurate, and low adherent. In this paper, we present a new interactive mobile system that enables automated food recognition and assessment based on user food images and provides dietary intervention while tracking users’ dietary and physical activities. In addition to using techniques in computer vision and machine learning, one unique feature of this system is the realization of real-time energy balance monitoring through metabolic network simulation. As a proof of concept, we have demonstrated the use of this system through an Android application.

We consider the problem of partitioning clinical services in hospitals into groups with the goal of efficiently allocating existing inpatient beds. At the strategic level, there are two major possibilities: pooling versus focusing. Pooling the bed capacity allows one to achieve an overall high occupancy level for a fixed number of beds. On the other hand, focusing by dividing the capacity into groups with restricted access may offer increased efficiency and better resource utilization. We first derive a 2-stage approach to address the 3-fold problem: 1) how many groups of services to form; 2) how many beds to allocate to each group; and 3) how to partition services among the groups. Specifically, Stage 1 uses cluster analysis utilizing the similarity principle for possible advantages of economies of scale. Stage 2 then incorporates utility/ benefit functions to optimize the partitions and allocation of beds. To contrast the results, we combine the two stages into a single mixed integer nonlinear program. Three full-scale examples demonstrate the flexibility and diverse application of our framework with managerial insights for different utility optimization goals and queuing systems. The resulting modeling framework is not computationally sensitive to the number of beds, making it more practical for usage by any hospitals.

Anticipatory guidance as a proactive developmentally based counselling technique that focuses on the need of a child at each stage of life. The prevention of dental problems is essential component of oral care particularly for haemophilic children. Parents should be educated and motivated regarding the value of prevention of dental caries, gingival and periodontal diseases, as well as dental trauma. Teething toys like a firm rubber or water filled plastic teething rings used during teething. Brushing twice daily with a fluoride toothpaste.1,000-ppm fluoride toothpaste for children under 7 years of age and 1,400-ppm fluoride toothpaste for people over 7 years of age. High sugar or acid content should be limited to mealtimes Most of the restorative procedures done without factor replacement. Use thin rubber dam, avoid retainers with sub gingival extensions, to protect interdental papilla wedged can be used. High speed vacuum saliva ejector should be used cautiously. Pulpotomy and pulpectomy is preferable to extraction. However, 30- 40% factor replacement is administered one hour prior to the extraction. This article discuss about anticipatory guidance in children with haemophilia.

Spread of ceftriaxone and ciprofloxacin resistant gonococci diseases demand new drug development as research have contradicted potent carbapenem and aminoglycoside antibiotics against Neisseria gonorrhoeae infections. Pubmed and GenBank analysis demonstrated only bla TEM and tetM genes present in N. gonorrhoeae plasmids where as in most MDR Enterobacteriaceae, hundred diversified beta-lactamase genes (blaOXA, blaCTX-M, blaCMY and blaNDM1) as well as many drug modified genes (aacA1/C1, catB3, aph, strA/B, sul1/2, aad, aph and aac(6’)-1b) are frequent in plasmids and chromosome. Thus existing knowledge on gonococci mdr genes is limited and merely few chromosomal drug efflux genes (DEGs=ermAB, mtrCDE, macAB etc.) and penicillin binding proteins (PBPs=ponA and penA) have assigned as cause of multi-resistance. It appeared that N. gonorrhoeae had limited life cycle outside the host limiting conjugation with other MDR-bacteria to acquire mdr genes easily. BLAST-search confirmed that every MDR N. gonorrhoeae genome did carry mtrD RND transporter gene linked to mtrC outer membrane efflux gene (MFS) similar to P. aeruginosa mexAB-family transporters. Further, macA/B transporters are involved in macrolide drug efflux and many mutations in penA, gyrA, mtrR and porB genes are maximum in MDR strains although mtrF and norA efflux genes are infrequent. We argue that plasmid mediated multi-resistance in gonococcal diseases needs to be reinvestigated and mutation theory (penA, gyrA, mtrR) may not sufficient to prove the worldwide spread of multi-drug resistant STDs.

Ketamine is considered a dissociative anesthetic medication, and it is a commonly administered by a parenteral route. It works mainly by blocking the N-methyl-D-aspartate (NMDA) receptor. It inhibits the voltage-gated Na_ and K_ channels and serotonin and dopamine re-uptake; also, it affects specific receptors, such as α-amino-3-hydroxy- 5-methyl-4-isoxazolepropionic acid (AMPA), kainite and amino butyric acid A receptors. Ketamine appears to have particular mechanisms that are potentially involved during analgesic induction, including enhancing of descending inhibition and anti-inflammatory effects. More recently, it has been shown that ketamine has potential in clinical practice for the management of chronic pain, cognitive function, depression, acute brain injury and disorders of the immune system.

Social media platforms have experienced a major growth in the past few years, with people choosing to communicate, very often publicly, through social media. They disseminate information, opinions, and announcements. They also share a lot about themselves and their experiences. In particular, they often share information about how they feel. This potentially provides a wealth of information, in real-time, about the emotional state of individuals or communities. This can, in turn, provide valuable information about how people react to various events.

Personalized patient education is a critical factor in the healthcare service delivery as it contributes to better management of diseases and ultimately enhanced clinical outcomes. Trans-Catheter Aortic Valve Implantation (TAVI) is a standard cardiac procedure for patients with severe aortic stenosis. TAVI is a minimally invasive procedure, however; this procedure is still associated with considerable risks based on the condition of the patient before performing TAVI. To obtain an informed consent, it is important to appropriately inform patients and their families about the risks and considerations associated with TAVI. Our research objective is to leverage digital health technologies to develop a personalized preoperative patient education system for TAVI patients. An iterative user-Centered approach was used to develop “TAVI System”, and its knowledge content is based on digitized evidence and clinical expertise. We used a knowledge management approach to model, computerize, and integrate TAVI patient assessment to generate personalized educational messages.