Syed Haque

Advances in Biomedical Informatics for the Management of Cancer

Abstract: Increased access to health care, and advances in education and technology have resulted in a larger proportion of the population having longer life expectancy. The strong correlation between age and cancer has resulted in a major healthcare problem for this century, and until recently cancer has defied any long‐lasting cure. However, progress, especially in the field of biomedical informatics, promises a successful prediction and possibly a permanent cure for cancer within the next two decades. Biomedical informatics—with its roots in computer science, biomedical engineering, biostatistics, and mathematics—helps to bring the patient closer to the physician, facilitates access to specialist information and knowledge bases across the world, and makes it possible to identify genetic expression profiles for malignant or cancerous cells. This paper reviews the new research findings in biomedical informatics, working toward the ultimate goal of successfully predicting cancer, solving complex problems in prevention and treatment of cancer, and perhaps completely curing the scourge of cancer.

A novel solution for maze traversal problems using artificial neural networks

In this paper we have addressed the problem of finding a path through a maze of a given size. The traditional ways of finding a path through a maze employ recursive algorithms in which unwanted or non-paths are eliminated in a recursive manner. Neural networks with their parallel and distributed nature of processing seem to provide a natural solution to this problem. We present a biologically inspired solution using a two level hierarchical neural network for the mapping of the maze as also the generation of the path if it exists. For a maze of size S the amount of time it takes would be a function of S (O(S)) and a shortest path (if more than one path exists) could be found in around S cycles where each cycle involves all the neurons doing their processing in a parallel manner. The solution presented in this paper finds all valid paths and a simple technique for finding the shortest path amongst them is also given. The results are very encouraging and more applications of the network setup used in this report are currently being investigated. These include synthetic modeling of biological neural mechanisms, traversal of decision trees, modeling of associative neural networks (as in relating visual and auditory stimuli of a given phenomenon) and surgical micro-robot trajectory planning and execution.

Prediction of hepatitis C using artificial neural network

The main objective of this research project is develop an expert system module, based on a back propagation feed forward artificial neural networks (ANNs), for the diagnosis of hepatitis C and compare its performance with other existing computer based decision support systems. The ANN based system was developed with a commercially available software package (Brain Maker, California scientific Software). Two different types of ANN models, unsupervised and supervised, were developed, compared, and tested. The predictive accuracy and the model training for supervised model was significantly better. The model was able to predict the Hepatitis C in patients very accurately, however performance was not significantly better than the traditional computer model based techniques. Further investigations are needed to understand the impact of this methodology on the outcome analysis. An existing database of hepatitis C infected patient was used. Data of 15 infected and 20 normal individual were collected. Dichotomous variables were coded as present (1) or not present (0). Continuous variable were recorded for patient age, ethnicity, patient number and patient sex. The results have been very interesting, however, some more research work is required to fine-tune the results. The main advantage of the developed system is that it is adaptive and self-adaptive type.

Absence of tubular proteinuria following environmental exposure to chromium

Certain chromium compounds are known to be nephrotoxic, but renal damage from long-term environmental or occupational exposure to chromium has not been documented. To detect possible preclinical renal damage, we tested the urine of 55 lifelong residents of an area contaminated with chromium landfill. The levels of four proteins were determined in urine samples: (1) human intestinal alkaline phosphatase, (2) tissue nonspecific alkaline phosphatase, (3) N-acetyl-beta-D-glucosaminidase, and (4) microalbumin. No elevated levels of proteins were found, and there were no significant correlations between urine protein and urine chromium concentrations. We concluded that long-term environmental exposure to chromium dust did not lead to tubular proteinuria.

A quantitative analysis of the effectiveness of laparascopy and endoscopy virtual reality simulators

Abstract The increasing use of virtual reality (VR) simulators in surgical training makes it imperative that definitive studies be performed to assess their training effectiveness. Indeed in this paper we report the meta-analysis of the efficacy of virtual reality simulators in (1) the transference of skills from the simulator training environment to the operating room and (2) their ability to discriminate between the experience levels of its users. The task completion time and the error score were the two study outcomes collated and analyzed in this meta-analysis. Sixteen studies were identified from a computer-based literature search (1996–2004). The meta-analysis of the random-effects model (because of the heterogeneity of the data) revealed that training on virtual reality simulators did lessen the time taken to complete a given surgical task as also clearly differentiate between the experienced and the novice trainees. Meta-analytic studies such as the one reported here would be very helpful in the planning and setting up of surgical training programs and for the establishment of reference ‘learning curves’ for a specific simulator and surgical task. If any such programs already exist they can then indicate the improvements to be made in the simulator used such as providing for more variety in their case scenarios based on the state and/or rate of learning of the trainee.

Electronic Medical Record Tobacco Use Vital Sign

ObjectiveDetermination of the prevalence of tobacco use and impact of tobacco prevention/treatment efforts in an electronic medical record enabled practice utilizing a defined tobacco vital sign variable.Design and MeasurementsRetrospective cohort study utilizing patient data recorded in an electronic medical record database between July 15, 2001, and May 31, 2003. Patient-reported tobacco use status was obtained for each of 6,771 patients during the pre-provider period of their 24,824 visits during the study period with the recorder blinded to past tobacco use status entries.ResultsAn overall current tobacco use prevalence of 27.1% was found during the study period. Tobacco use status was recorded in 96% of visits. Comparison of initial to final visit tobacco use status demonstrates a consistency rate of 75.0% declaring no change in tobacco status in the 4,522 patients with two or more visits. An 8.6% net tobacco use decline was seen for the practice (p value < 0.001).ConclusionSelf reported tobacco use status as a vital sign embedded within the workflow of an electronic medical record enabled practice was a quantitative tool for determination of tobacco use prevalence and a measuring stick of risk prevention/intervention impact.

Diagnostic efficacy value in terms of sensitivity and specificity of imaging modalities in detecting the abdominal aortic aneurysm: a systematic review

The purpose of this study was to examine whether duplex ultrasonography (DUS) or MR angiography (MRA) or CT angiography (CTA) is more applicable to use as alternative modality in terms of sensitivity and specificity for detection of abdominal aortic aneurysm (AAA). A search of the medical databases was performed for describing AAA evaluation and detection. Twenty eight studies were found and met the selection criteria. Diameter of aneurysms was categorised by size: ≤ 2.5 cm of the aneurysm diameter. For aneurisms ≤ 2.5 cm, the mean reported sensitivities and specificities were DUS: 81% and 91.1%; CTA: 84.3% and 98.4%; MRA: 95.8% and 95.8%, respectively compared DSA as gold standard. MRA has the highest sensitivity and CTA has the highest specificity reported diagnostic accuracy in detecting the aneurysm ≤ 2.5 cm of AAA diameter and they could be used as a reliable alternative modality to invasive DSA.

Analysis of the incidence of lung cancer based on anatomical sites of lung using NIS data

Analysis concludes that the risk occurrence of lung cancer follows an order from high to low: upper lobe, lower lobe, other-parts of the lung, main bronchus, and middle lobe. We have also examined the association of each category of lung with gender and race too. The overall lung cancer analysis indicate that White and Black Americans have the higher risk of getting lung cancer as compared with other races, but anatomical category of lung cancer indicates White American are more susceptible to each category of lung except other-part of lung as compared with other races. The odds ratio analysis for each anatomical site concludes White male and female [odds ratio of all sub category – male/female 1.03 to 1.08] are equally susceptible to each category of lung. The Black females [odds ratio of lower lobe-male/female 1.08] are highly associated with lower lobe lung cancer as compared with Black males while Hispanic, Asian and Native American females are more associated with middle lobe lung cancer as compared with Hispanic, Asian and native American males [odds ratio for middle lobe – male/female 0.89 to 0.95].

Biomedical informatics education for capacity building in developing countries

Biomedical informatics is widely recognised as the defining scientific endeavour of the twenty-first century with profound impacts throughout our societies and economies. It provides the potential to achieve the desirable objectives of lessening poverty and disease burden in the developing nations. But the lack of biomedical informatics education and research infrastructure in the developing countries remains a major barrier both to the development of biomedical informatics as a discipline and to the sustainability of the implemented solutions of any domestically or externally financed pilot projects in wealth and healthcare development. This paper puts forth some important components that would constitute a science based, long-term, sustainable biomedical informatics education, training and research policy framework. These components are what are already incorporated into similar such policy frameworks in the developed nations and some of the emergent economies in the developing nations as well.

Expert system for the diagnosis of neonatal jaundice for use by medical field personnel

The main objective of this project is to develop an expert system module that uses the clinical decision criteria of experts in the neonatology field to advice paramedical and semi-skilled personnel who require guidance to diagnose the etiology of neonatal jaundice. The project was developed with a commercially available software package EXSYS (Multilogic Inc.). In this project, we have used a rule-based system to build the decision tree that would aid the paramedical personnel to arrive at a appropriate etiology for hyperbilirubinemia in a neonate. The project is field tested in India, where the residents are asked to come up with the correct diagnosis given the clinical tests. The disadvantage of this model is that there is the problem of it becoming obsolete in a few years time unless it is constantly being updated by developers. There is also the problem that this system cannot train or learn by itself unlike an artificial neural network.