Abstract: Breast cancer is one of the most frequent occurring cancers in women throughout the world including U.K. The grading of this cancer plays a vital role in the prognosis of the disease. In this paper we present an overview of the use of advanced computational method of fuzzy inference system as a tool for the automation of breast cancer grading. A new spectral data set obtained from Fourier Transform Infrared Spectroscopy (FTIR) of cancer patients has been used for this study. The future work outlines the potential areas of fuzzy systems that can be used for the automation of breast cancer grading.
Abstract: TTV is an unenveloped circular single-stranded DNA
virus with a diameter of 30-32 nm that first was described in 1997 in
Japan. TTV was detected in various populations without proven
pathology, including blood donors and in patients with chronic HBV
and HCV hepatitis. The aim of this study was to determine the
prevalence of TTV DNA in Iranian patients with chronic hepatitis B
and C. Viral TTV-DNA was studied in 442 samples (202 with HBV,
138 with HCV and 102 controls) collected from west south of Iran.
All extracted serum DNA was amplified by TTV ORF1 gene specific
primers using the semi nested PCR technique. TTV DNA was
detected in the serum of 8.9% and 10.8% patients with chronic
hepatitis B and C, respectively. Prevalence of TTV-DNA in the serum
of 102 controls was 2.9%. Results showed significant relation of TTV
with HBV and HCV in patients by using T test examination (P
Abstract: Combined therapy using Interferon and Ribavirin is the standard treatment in patients with chronic hepatitis C. However, the number of responders to this treatment is low, whereas its cost and side effects are high. Therefore, there is a clear need to predict patient’s response to the treatment based on clinical information to protect the patients from the bad drawbacks, Intolerable side effects and waste of money. Different machine learning techniques have been developed to fulfill this purpose. From these techniques are Associative Classification (AC) and Decision Tree (DT). The aim of this research is to compare the performance of these two techniques in the prediction of virological response to the standard treatment of HCV from clinical information. 200 patients treated with Interferon and Ribavirin; were analyzed using AC and DT. 150 cases had been used to train the classifiers and 50 cases had been used to test the classifiers. The experiment results showed that the two techniques had given acceptable results however the best accuracy for the AC reached 92% whereas for DT reached 80%.
Abstract: Synchronization between 0.1 Hz oscillations in heart rate and blood pressure is studied and its change during vertical tilt is evaluated in 37 myocardial infarction patients. Two groups of patients are identified with decreased and increased, respectively, synchronization of the studied oscillations as a response to a tilt test. It is shown that assessment of synchronization of 0.1 Hz oscillations as a response to vertical tilt can be used as a guideline for selecting optimal dose of beta-blocker treatment in post-myocardial infarction patients.
Abstract: Viral influenza A subtypes H5N1 and pandemic
H1N1 (pH1N1) have worldwide emerged and transmitted. The most
common anti-influenza drug for treatment of both seasonal and
pandemic influenza viruses is oseltamivir that nowadays becomes
resistance to influenza neuraminidase. The novel long-acting drug,
laninamivir, was discovered for treatment of the patients infected
with influenza B and influenza A viruses. In the present study,
laninamivir complexed with wild-type strain of both H5N1 and
pH1N1 viruses were comparatively determined the structures and
drug-target interactions by means of molecular dynamics (MD)
simulations. The results show that the hydrogen bonding interactions
formed between laninamivir and its binding residues are likely
similar for the two systems. Additionally, the presence of
intermolecular interactions from laninamivir to the residues in the
binding pocket is established through their side chains in accordance
with hydrogen bond interactions.
Abstract: Leprosy is an infectious disease caused by
Mycobacterium Leprae, this disease, generally, compromises
the neural fibers, leading to the development of disability.
Disabilities are changes that limit daily activities or social life
of a normal individual. When comes to leprosy, the study of
disability considered the functional limitation (physical
disabilities), the limitation of activity and social participation,
which are measured respectively by the scales: EHF, SALSA
and PARTICIPATION SCALE. The objective of this work is
to propose an on-line monitoring of leprosy patients, which is
based on information scales EHF, SALSA and
PARTICIPATION SCALE. It is expected that the proposed
system is applied in monitoring the patient during treatment
and after healing therapy of the disease. The correlations that
the system is between the scales create a variety of
information, presented the state of the patient and full of
changes or reductions in disability. The system provides
reports with information from each of the scales and the
relationships that exist between them. This way, health
professionals, with access to patient information, can
intervene with techniques for the Prevention of Disability.
Through the automated scale, the system shows the level of
the patient and allows the patient, or the responsible, to take a
preventive measure. With an online system, it is possible take
the assessments and monitor patients from anywhere.
Abstract: Today-s healthcare industries had become more
patient-centric than profession-centric, from which the issues of quality of healthcare and the patient safety are the major concerns in the modern healthcare facilities. An unplanned extubation (UE) may
be detrimental to the patient-s life, and thus is one of the major indexes
of patient safety and healthcare quality. A high UE rate not only
defeated the healthcare quality as well as the patient safety policy but
also the nurses- morality, and job satisfaction. The UE problem in a psychiatric hospital is unique and may be a tough challenge for the
healthcare professionals for the patients were mostly lacking communication capabilities. We reported with this essay a particular
project that was organized to reduce the UE rate from the current 2.3%
to a lower and satisfactory level in the long-term care units of a psychiatric hospital. The project was conducted between March 1st,
2011 and August 31st, 2011. Based on the error information gathered
from varied units of the hospital, the team analyzed the root causes
with possible solutions proposed to the meetings. Four solutions were
then concluded with consensus and launched to the units in question.
The UE rate was now reduced to a level of 0.17%. Experience from
this project, the procedure and the tools adopted would be good reference to other hospitals.
Abstract: Purpose: To explore the use of Curvelet transform to
extract texture features of pulmonary nodules in CT image and support
vector machine to establish prediction model of small solitary
pulmonary nodules in order to promote the ratio of detection and
diagnosis of early-stage lung cancer. Methods: 2461 benign or
malignant small solitary pulmonary nodules in CT image from 129
patients were collected. Fourteen Curvelet transform textural features
were as parameters to establish support vector machine prediction
model. Results: Compared with other methods, using 252 texture
features as parameters to establish prediction model is more proper.
And the classification consistency, sensitivity and specificity for the
model are 81.5%, 93.8% and 38.0% respectively. Conclusion: Based
on texture features extracted from Curvelet transform, support vector
machine prediction model is sensitive to lung cancer, which can
promote the rate of diagnosis for early-stage lung cancer to some
extent.
Abstract: Acoustical properties of speech have been shown to
be related to mental states of speaker with symptoms: depression
and remission. This paper describes way to address the issue of
distinguishing depressed patients from remitted subjects based on
measureable acoustics change of their spoken sound. The vocal-tract
related frequency characteristics of speech samples from female
remitted and depressed patients were analyzed via speech
processing techniques and consequently, evaluated statistically by
cross-validation with Support Vector Machine. Our results
comparatively show the classifier's performance with effectively
correct separation of 93% determined from testing with the subjectbased
feature model and 88% from the frame-based model based on
the same speech samples collected from hospital visiting interview
sessions between patients and psychiatrists.
Abstract: Surgical site infections (SSIs) are the most common
nosocomial infection in surgical patients resulting in significant
increases in postoperative morbidity and mortality. The commonly
causative bacteria developed resistance to virtually all antibiotics
available. The aim of this study was to isolation and identification the
most common bacteria that cause SSIs in Medical Research Institute,
and to compare their sensitivity to selected group of antibiotics and
natural products (garlic, oregano, olive, and Nigella sativa oils). The
isolated pathogens collected from infected surgical wounds were
identified, and their sensitivities to the antibiotics commonly
available for clinical use, and also to the different concentrations of
the used natural products were investigated. The results indicate to
the potential therapeutic effect of the tested natural products in
treatment of surgical wound infections.
Abstract: This paper presents a new strategy of identification
and classification of pathological voices using the hybrid method
based on wavelet transform and neural networks. After speech
acquisition from a patient, the speech signal is analysed in order to
extract the acoustic parameters such as the pitch, the formants, Jitter,
and shimmer. Obtained results will be compared to those normal and
standard values thanks to a programmable database. Sounds are
collected from normal people and patients, and then classified into
two different categories. Speech data base is consists of several
pathological and normal voices collected from the national hospital
“Rabta-Tunis". Speech processing algorithm is conducted in a
supervised mode for discrimination of normal and pathology voices
and then for classification between neural and vocal pathologies
(Parkinson, Alzheimer, laryngeal, dyslexia...). Several simulation
results will be presented in function of the disease and will be
compared with the clinical diagnosis in order to have an objective
evaluation of the developed tool.
Abstract: The argument that self-disclosure will change the
psychoanalytic process into a socio-cultural niche distorting the
therapeutic alliance and compromise therapeutic effectiveness is still
the widely held belief amongst many psychotherapists. This paper
considers the issues surrounding culture, disclosure and concealment
since they remain largely untheorized and clinically problematic. The
first part of the paper will critically examine the theory and practice
of psychoanalysis across cultures, and explore the reasons for
culturally diverse patients to conceal rather than disclose their
feelings and thoughts in the transference. This is followed by a
discussion on how immigrant analysts- anonymity is difficult to
maintain since diverse nationalities, language and accents provide
clues to the therapist-s and patient-s origins. Through personal
clinical examples of one the author-s (who is an immigrant) the paper
analyses the transference-countertransference paradigm and how it
reflects in the analyst-s self-revelation.
Abstract: Human amniotic membrane (HAM) is a useful
biological material for the reconstruction of damaged ocular surface.
The processing and preservation of HAM is critical to prevent the
patients undergoing amniotic membrane transplant (AMT) from cross
infections. For HAM preparation human placenta is obtained after an
elective cesarean delivery. Before collection, the donor is screened
for seronegativity of HCV, Hbs Ag, HIV and Syphilis. After
collection, placenta is washed in balanced salt solution (BSS) in
sterile environment. Amniotic membrane is then separated from the
placenta as well as chorion while keeping the preparation in BSS.
Scrapping of HAM is then carried out manually until all the debris is
removed and clear transparent membrane is acquired. Nitrocellulose
membrane filters are then placed on the stromal side of HAM, cut
around the edges with little membrane folded towards other side
making it easy to separate during surgery. HAM is finally stored in
solution of glycerine and Dulbecco-s Modified Eagle Medium
(DMEM) in 1:1 ratio containing antibiotics. The capped borosil vials
containing HAM are kept at -80°C until use. This vial is thawed to
room temperature and opened under sterile operation theatre
conditions at the time of surgery.
Abstract: Diabetes Mellitus is a chronic metabolic disorder, where the improper management of the blood glucose level in the diabetic patients will lead to the risk of heart attack, kidney disease and renal failure. This paper attempts to enhance the diagnostic accuracy of the advancing blood glucose levels of the diabetic patients, by combining principal component analysis and wavelet neural network. The proposed system makes separate blood glucose prediction in the morning, afternoon, evening and night intervals, using dataset from one patient covering a period of 77 days. Comparisons of the diagnostic accuracy with other neural network models, which use the same dataset are made. The comparison results showed overall improved accuracy, which indicates the effectiveness of this proposed system.
Abstract: This study mainly aims at assessing the level of
microbial pollution of the water used in the chair system in dental
clinics. For this purpose 36 samples have been randomly collected
from a number of dental surgeries in the city of Tripoli in Libya.
However, 32 of the samples have tested positive to microbial
pollution including 13 of the samples, which have tested positives to
Pseudomonas aeruginosa. Based on the results of the test a further
investigation of the biofilms incorporated within the dental chair
system has been conducted. The laboratory tests of biofilms with
similar design to those found in dental chairs have proved that
bacterial pollution takes place through saliva of the patients who use
the chairs, and that this saliva is rich with nutrients which provides a
suitable breeding ground for all types of bacteria.
Abstract: Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.
Abstract: Functional gastrointestinal disorders affect millions of people spread all age regardless of race and sex. There are, however, rare diagnostic methods for the functional gastrointestinal disorders because functional disorders show no evidence of organic and physical causes. Our research group identified recently that the gastrointestinal tract well in the patients with the functional gastrointestinal disorders becomes more rigid than healthy people when palpating the abdominal regions overlaying the gastrointestinal tract. Aim of this study is, therefore, to develop a diagnostic system for the functional gastrointestinal disorders based on ultrasound technique, which can quantify the characteristic above related to the rigidity of the gastrointestinal tract well. Ultrasound system was designed. The system consisted of transmitter, ultrasonic transducer, receiver, TGC, and CPLD, and verified via a phantom test. For the phantom test, ten soft-tissue specimens were harvested from porcine. Five of them were then treated chemically to mimic a rigid condition of gastrointestinal tract well, which was induced by functional gastrointestinal disorders. Additionally, the specimens were tested mechanically to identify if the mimic was reasonable. The customized ultrasound system was finally verified through application to human subjects with/without functional gastrointestinal disorders (Normal and Patient Groups). It was identified from the mechanical test that the chemically treated specimens were more rigid than normal specimen. This finding was favorably compared with the result obtained from the phantom test. The phantom test also showed that ultrasound system well described the specimen geometric characteristics and detected an alteration in the specimens. The maximum amplitude of the ultrasonic reflective signal in the rigid specimens (0.2±0.1Vp-p) at the interface between the fat and muscle layers was explicitly higher than that in the normal specimens (0.1±0.0Vp-p). Clinical tests using our customized ultrasound system for human subject showed that the maximum amplitudes of the ultrasonic reflective signals near to the gastrointestinal tract well for the patient group (2.6±0.3Vp-p) were generally higher than those in normal group (0.1±0.2Vp-p). Here, maximum reflective signals was appeared at 20mm depth approximately from abdominal skin for all human subjects, corresponding to the location of the boundary layer close to gastrointestinal tract well. These results suggest that newly designed diagnostic system based on ultrasound technique may diagnose enough the functional gastrointestinal disorders.
Abstract: An accident is an unexpected and unplanned situation
that happens and affects human in a negative outcome. The accident
can cause an injury to a human biological organism. Thus, the
provision of initial care for an illness or injury is very important
move to prepare the patients/victims before sending to the doctor. In
this paper, a First Aid Application is developed to give some
directions for preliminary taking care of patient/victim via Android
mobile device. Also, the navigation function using Google Maps API
is implemented in this paper for searching a suitable path to the
nearest hospital. Therefore, in the emergency case, this function can
be activated and navigate patients/victims to the hospital with the
shortest path.
Abstract: Background, measuring an individual-s Health
Literacy is gaining attention, yet no appropriate instrument is available
in Taiwan. Measurement tools that were developed and used in
western countries may not be appropriate for use in Taiwan due to a
different language system. Purpose of this research was to develop a
Health Literacy measurement instrument specific for Taiwan adults.
Methods, several experts of clinic physicians; healthcare
administrators and scholars identified 125 common used health related
Chinese phrases from major medical knowledge sources that easy
accessible to the public. A five-point Likert scale is used to measure
the understanding level of the target population. Such measurement is
then used to compare with the correctness of their answers to a health
knowledge test for validation. Samples, samples under study were
purposefully taken from four groups of people in the northern
Pingtung, OPD patients, university students, community residents,
and casual visitors to the central park. A set of health knowledge index
with 10 questions is used to screen those false responses. A sample
size of 686 valid cases out of 776 was then included to construct this
scale. An independent t-test was used to examine each individual
phrase. The phrases with the highest significance are then identified
and retained to compose this scale. Result, a Taiwan Health Literacy
Scale (THLS) was finalized with 66 health-related phrases under nine
divisions. Cronbach-s alpha of each division is at a satisfactory level
of 89% and above. Conclusions, factors significantly differentiate the
levels of health literacy are education, female gender, age, family
members of stroke victims, experience with patient care, and
healthcare professionals in the initial application in this study..
Abstract: Deep Brain Stimulation or DBS is the second solution
for Parkinson's Disease. Its three parameters are: frequency, pulse
width and voltage. They must be optimized to achieve successful
treatment. Nowadays it is done clinically by neurologists and there is
not certain numerical method to detect them. The aim of this research
is to introduce simulation and modeling of Parkinson's Disease
treatment as a computational procedure to select optimum voltage.
We recorded finger tremor signals of some Parkinsonian patients
under DBS treatment at constant frequency and pulse width but
variable voltages; then, we adapted a new model to fit these data. The
optimum voltages obtained by data fitting results were the same as
neurologists- commented voltages, which means modeling can be
used as an engineering method to select optimum stimulation
voltages.