SMS-based medical diagnostic telemetry data transmission protocol for medical sensors

People with special medical monitoring needs can, these days, be sent home and remotely monitored through the use of data logging medical sensors and a transmission base-station. While this can improve quality of life by allowing the patient to spend most of their time at home, most current technologies rely on hardwired landline technology or expensive mobile data transmissions to transmit data to a medical facility. The aim of this paper is to investigate and develop an approach to increase the freedom of a monitored patient and decrease costs by utilising mobile technologies and SMS messaging to transmit data from patient to medico. To this end, we evaluated the capabilities of SMS and propose a generic communications protocol which can work within the constraints of the SMS format, but provide the necessary redundancy and robustness to be used for the transmission of non-critical medical telemetry from data logging medical sensors.

Mycobacterium ulcerans infection : factors influencing diagnostic delay

Objective: To document the epidemiology, clinical characteristics and diagnosis of an outbreak of Mycobacterium ulcerans infection (Bairnsdale or Buruli ulcer [BU]) during the period 1998–2006, and compare delays in diagnosis between residents of endemic and non-endemic regions.

Design and setting: Retrospective case study of patients identified through infectious disease physicians on the Bellarine Peninsula and the Victorian Department of Human Services notifiable diseases database.

Main outcome measures: Description of events leading to diagnosis of BU.

Results: Eighty-five BU patients recalled their experience. Fifty-three patients were older than 60 years, and 61 permanently resided on the Bellarine Peninsula. The onset of symptoms occurred most frequently in mid winter. Twenty-eight patients had lesions on the arm and 51 on the leg. The median time between onset of symptoms and first medical contact was shorter for those living in the endemic area (3.0 weeks; interquartile range [IQR], 1.0–5.0 weeks) compared with non-endemic areas (5.3 weeks; IQR, 2.0–9.5 weeks) (P = 0.05). Patients who resided in the endemic area had a shorter median time from their first medical appointment to diagnosis (1.0 week; IQR, 0.0–3.9 weeks) than those who resided in non-endemic areas (5.0 weeks; IQR, 1.3–8.0 weeks) (P = 0.001).

Conclusion: Delay in presentation and time to diagnosis of BU are longer in non-endemic than endemic areas. Measures should be taken to raise awareness of the disease in non-endemic areas.

Robust-diagnostic regression : a prelude for inducing reliable knowledge from regression

Regression lies heart in statistics, it is the one of the most important branch of multivariate techniques available for extracting knowledge in almost every field of study and research. Nowadays, it has drawn a huge interest to perform the tasks with different fields like machine learning, pattern recognition and data mining. Investigating outlier (exceptional) is a century long problem to the data analyst and researchers. Blind application of data could have dangerous consequences and leading to discovery of meaningless patterns and carrying to the imperfect knowledge. As a result of digital revolution and the growth of the Internet and Intranet data continues to be accumulated at an exponential rate and thereby importance of detecting outliers and study their costs and benefits as a tool for reliable knowledge discovery claims perfect attention. Investigating outliers in regression has been paid great value for the last few decades within two frames of thoughts in the name of robust regression and regression diagnostics. Robust regression first wants to fit a regression to the majority of the data and then to discover outliers as those points that possess large residuals from the robust output whereas in regression diagnostics one first finds the outliers, delete/correct them and then fit the regular data by classical (usual) methods. At the beginning there seems to be much confusion but now the researchers reach to the consensus, robustness and diagnostics are two complementary approaches to the analysis of data and any one is not good enough. In this chapter, we discuss both of them under the unique spectrum of regression diagnostics. Chapter expresses the necessity and views of regression diagnostics as well as presents several contemporary methods through numerical examples in linear regression within each aforesaid category together with current challenges and possible future research directions. Our aim is to make the chapter self-explained maintaining its general accessibility.

Nano-lactoferrin in diagnostic, imaging and targeted delivery for cancer and infectious diseases

Lactoferrin (Lf) is a natural occurring iron binding protein present in many mammalian excretions and involved in various physiological processes. Lf is used in the transport of iron along with other molecules and ions from the digestive system. However its the modulatory functions exhibited by Lf in connection to immune response, disease regression and diagnosis that has made this protein an attractive therapeutic against chronic diseases. Further, the exciting potentials of employing nanotechnology in advancing drug delivery systems, active disease targeting and prognosis have also shown some encouraging outcomes. This review focuses on the role of Lf in diagnosing infection, cancer, neurological and inflammatory diseases and the recent nanotechnology based strategies.