On Interpretability of Deep Learning based Skin Lesion Classifiers using Concept Activation Vectors

Deep learning based medical image classifiers have shown remarkable prowess in various application areas like ophthalmology, dermatology, pathology, and radiology. However, the acceptance of these Computer-Aided Diagnosis (CAD) systems in real clinical setups is severely limited primarily because their decision-making process remains largely obscure. This work aims at elucidating a deep learning based medical image classifier by verifying that the model learns and utilizes similar disease-related concepts as described and employed by dermatologists. We used a well-trained and high performing neural network developed by REasoning for COmplex Data (RECOD) Lab for classification of three skin tumours, i.e. Melanocytic Naevi, Melanoma and Seborrheic Keratosis and performed a detailed analysis on its latent space. Two well established and publicly available skin disease datasets, PH2 and derm7pt, are used for experimentation. Human understandable concepts are mapped to RECOD image classification model with the help of Concept Activation Vectors (CAVs), introducing a novel training and significance testing paradigm for CAVs. Our results on an independent evaluation set clearly shows that the classifier learns and encodes human understandable concepts in its latent representation. Additionally, TCAV scores (Testing with CAVs) suggest that the neural network indeed makes use of disease-related concepts in the correct way when making predictions. We anticipate that this work can not only increase confidence of medical practitioners on CAD but also serve as a stepping stone for further development of CAV-based neural network interpretation methods.Comment: Accepted for the IEEE International Joint Conference on Neural Networks (IJCNN) 202

Diagnostic Yield of Blood Cultures among Patients Admitted with Non-Focal Pyrexias

OBJECTIVES To establish the diagnostic yield of blood cultures among patients admitted with non-focal pyrexias. METHODOLOGY This descriptive cross-sectional study was conducted in the Department of Medicine, Khyber Teaching Hospital, Peshawar, from August 2020 to April 2021. One hundred ninety-seven patients with non-focal pyrexia were recruited. Data about age, gender, presence of other illnesses like diabetes and hypertension, history of smoking and duration of fever were noted. A thorough clinical evaluation was done. Under aseptic conditions, 2 blood culture sets were taken. The final blood culture report was collected after 5 days of incubation in culture media. The culture was labelled positive if any organism was isolated from the sample. All data was entered in specially designed proforma. Patients with positive blood cultures were managed as per hospital protocols. Confidentiality of data was ensured. RESULTSOur study shows that among 197 patients, 18(9%) had positive cultures, while 179(91%) did not yield any pathogen on blood culture. Escherichia coli was the most commonly grown organism among the positive blood cultures. CONCLUSION The yield of blood culture was 9% in febrile patients admitted to the medical ward of a tertiary care hospital

Peace Perceptions Of Prospective Teachers For Promoting Peace Activities For School Settings In Pakistan

Peace has been recognized as a matter of education and to be promoted at the initial level.  The present study attempts to generate a profile of activities toward peace education among prospective teachers.  The Nominal Group Technique (NGT) was used by selecting fifteen prospective teachers as a Nominal Group (NG). NGT was applied under a sequence of stages (idea generating, selection, listing, clarification, ranking and consensus stages). Results generated from the NGT were organized into three categories of student-related activities, teacher-focused activities, and administration and community- related activities. Participants’ preferences were higher for activities that included individual practical participation. Participation in the Action Research process was ranked at the  bottom. Tentative conclusions are drawn with regard to teacher education and peace studies

The Higher The Quality Of Teaching The Higher The Quality Of Education

The higher education plays as leadership role in the system of education. Quality education can ensure security, welfare and prosperity of a nation. The key factors influencing the quality of higher education is the quality of faculty, curriculum standards, technological infrastructure available, research environment, accreditation regime, administrative policies, financing, evaluation and good governance. The main objectives of the study were (1) To evaluate the indicators of good teaching. (2) To examine the institutional policies for valuing the teaching. (3) To examine the contribution of teaching towards professional development of teachers. (4) To find out institutional efforts for enhancing the professional development of teachers. For study purposes five federal universities of Islamabad were taken and their faculties were included in the population. Twenty teachers of each university were taken as the sample of the study. This sample was selected with the help of the students from each department. As students are considered tougher evaluators of the teachers so the selection of the good teachers was completed on the basis of the five common competencies such as competencies related to subject and subject area teaching, competencies related to teaching and learning, competencies in research work and competencies related to professional behaviour .This survey type study was conducted through a questionnaire. The study concluded that good teaching does not pay any benefit to teachers except self-satisfaction and also finding that the requirements for quality teaching are not available in universities. The present study recommends the higher quality of teaching may be ranked and recognized at local, national and international level

Diversity Of Desired And Observed Levels Of Qualities Among Teacher Candidates Perceived By Private School Management

The trend of enrolment in private schools is growing rapidly. The criteria of quality for teacher candidates is complex one, great value is placed for oral interviews along with other formal techniques of selection process. The present study focused to investigate the desired and observed levels of qualities for teacher candidates perceived by their employers at private educational institutions in Pakistan. Interviews of personnel involved in selection process, a focus group discussion and a survey were used as the research method. After semi-structured interview with 20 employers the initial three levels of dimensions of qualities for teacher candidates i.e. dimensions of educational and professional knowledge; dimensions of teaching and professional skills; and dimensions of values and attitudes were developed and kept for  focus group discussion. In this way six qualities for each dimension were finalized and the survey was conducted to rate the desired and observed levels of 18 items. A total number of 139 responses were available through this survey. The mean of desired and observed responses for each item was calculated. The difference between means, standard deviations and t-values were also calculated. The differences in mean values for desired and observed levels for all three categories indicate that employers of private schools are not satisfied with the output of teachers training programs

Causes Of Male Dropout Rate In Pakistan

This study aimed to seek the cause of male students’ dropout rate at the primary level of F.R. Peshawar. The main objectives of the study were:  1) to study the teacher problems and attitudes of the dropouts, 2) to determine the factors that cause dropouts, 3) to study the government’s strategy of dropouts, and 4) to provide suggestions to overcome this problem and improve the literacy rate. The simple random sampling technique was used and the researchers selected ten schools of F.R. Peshawar Asho khel. The research study was descriptive in nature. Three types of questionnaires were prepared - one for teachers, one for students, and one for parents. The researcher then collected data, tabulated, analyzed, and interpreted it in a percentage method. On the basis of analysis, it was concluded that the majority of teachers viewed themselves as being responsible for dropouts due to corporal punishment and poor attention given to the students. The majority of students opined that they themselves are responsible for dropping out due to fear of teachers, failure of examinations, mental weaknesses, and being weak in math and English. The majority of parents viewed that they are responsible for their children’s dropping out due to their poverty, illiteracy, and unawareness of the importance of education. The following recommendations were made for improvement of the teaching-learning situation in primary education institutions: 1) Teachers should show fair attitudes and behave well; 2) The government should appoint talented and local teachers in the area; 3) Teachers may improve and provide a variety of motivation techniques in different teaching situations; 4) The government should provide full attention to their education system by providing financial support to poor students in the form of scholarships; and 5) The government should facilitate the teachers and increase their salaries

Neuroprotection with metformin and thymoquinone against ethanol-induced apoptotic neurodegeneration in prenatal rat cortical neurons

<p>Abstract</p> <p>Background</p> <p>Exposure to ethanol during early development triggers severe neuronal death by activating multiple stress pathways and causes neurological disorders, such as fetal alcohol effects or fetal alcohol syndrome. This study investigated the effect of ethanol on intracellular events that predispose developing neurons for apoptosis via calcium-mediated signaling. Although the underlying molecular mechanisms of ethanol neurotoxicity are not completely determined, mitochondrial dysfunction, altered calcium homeostasis and apoptosis-related proteins have been implicated in ethanol neurotoxicity. The present study was designed to evaluate the neuroprotective mechanisms of metformin (Met) and thymoquinone (TQ) during ethanol toxicity in rat prenatal cortical neurons at gestational day (GD) 17.5.</p> <p>Results</p> <p>We found that Met and TQ, separately and synergistically, increased cell viability after ethanol (100 mM) exposure for 12 hours and attenuated the elevation of cytosolic free calcium [Ca²⁺]_c. Furthermore, Met and TQ maintained normal physiological mitochondrial transmembrane potential (Δψ_M), which is typically lowered by ethanol exposure. Increased cytosolic free [Ca²⁺]_cand lowered mitochondrial transmembrane potential after ethanol exposure significantly decreased the expression of a key anti-apoptotic protein (Bcl-2), increased expression of Bax, and stimulated the release of cytochrome-c from mitochondria. Met and TQ treatment inhibited the apoptotic cascade by increasing Bcl-2 expression. These compounds also repressed the activation of caspase-9 and caspase-3 and reduced the cleavage of PARP-1. Morphological conformation of cell death was assessed by TUNEL, Fluoro-Jade-B, and PI staining. These staining methods demonstrated more cell death after ethanol treatment, while Met, TQ or Met plus TQ prevented ethanol-induced apoptotic cell death.</p> <p>Conclusion</p> <p>These findings suggested that Met and TQ are strong protective agents against ethanol-induced neuronal apoptosis in primary rat cortical neurons. The collective data demonstrated that Met and TQ have the potential to ameliorate ethanol neurotoxicity and revealed a possible protective target mechanism for the damaging effects of ethanol during early brain development.</p

GAN-driven Electromagnetic Imaging of 2-D Dielectric Scatterers

Inverse scattering problems are inherently challenging, given the fact they are ill-posed and nonlinear. This paper presents a powerful deep learning-based approach that relies on generative adversarial networks to accurately and efficiently reconstruct randomly-shaped two-dimensional dielectric objects from amplitudes of multi-frequency scattered electric fields. An adversarial autoencoder (AAE) is trained to learn to generate the scatterer's geometry from a lower-dimensional latent representation constrained to adhere to the Gaussian distribution. A cohesive inverse neural network (INN) framework is set up comprising a sequence of appropriately designed dense layers, the already-trained generator as well as a separately trained forward neural network. The images reconstructed at the output of the inverse network are validated through comparison with outputs from the forward neural network, addressing the non-uniqueness challenge inherent to electromagnetic (EM) imaging problems. The trained INN demonstrates an enhanced robustness, evidenced by a mean binary cross-entropy (BCE) loss of $0.13$ and a structure similarity index (SSI) of $0.90$. The study not only demonstrates a significant reduction in computational load, but also marks a substantial improvement over traditional objective-function-based methods. It contributes both to the fields of machine learning and EM imaging by offering a real-time quantitative imaging approach. The results obtained with the simulated data, for both training and testing, yield promising results and may open new avenues for radio-frequency inverse imaging