Machine Learning with Abstention for Automated Liver Disease Diagnosis

This paper presents a novel approach for detection of liver abnormalities in an automated manner using ultrasound images. For this purpose, we have implemented a machine learning model that can not only generate labels (normal and abnormal) for a given ultrasound image but it can also detect when its prediction is likely to be incorrect. The proposed model abstains from generating the label of a test example if it is not confident about its prediction. Such behavior is commonly practiced by medical doctors who, when given insufficient information or a difficult case, can chose to carry out further clinical or diagnostic tests before generating a diagnosis. However, existing machine learning models are designed in a way to always generate a label for a given example even when the confidence of their prediction is low. We have proposed a novel stochastic gradient based solver for the learning with abstention paradigm and use it to make a practical, state of the art method for liver disease classification. The proposed method has been benchmarked on a data set of approximately 100 patients from MINAR, Multan, Pakistan and our results show that the proposed scheme offers state of the art classification performance.Comment: Preprint version before submission for publication. complete version published in proc. 15th International Conference on Frontiers of Information Technology (FIT 2017), December 18-20, 2017, Islamabad, Pakistan. http://ieeexplore.ieee.org/document/8261064

Job Stress of Academia and its Effect on their Performance in Public Sector Universities of Punjab

The study was aimed to examine the job stress of academia and its effects on their performance in public sector universities of Punjab. The objectives were to identify the nature of job stress, factors responsible for job stress, and relationship between job stress and performance of academia. There were nine regions in the Punjab. Seven universities representing each region were the population of the study. These universities were, PU from Lahore, BZU from Multan, PMAS-Arid from Rawalpindi, UOS form Sargodha, UOG from Gujrat, IUB from Bahawalpur and GCU from Faisalabad. Stratified random sampling techniques were used and strata were made with respect to the population of the study. A sample of 373 academic heads, 434 academia and 1008 students were taken for study. It was concluded from the results that academia stress is multiple factor construct, and these entire factors associated with each other’s. It is also found from academia job stress negatively effect on their performance. It was recommended from results that university as an organization may conduct need assessment program for academia to explore the causes of their stress and dissatisfaction

Link adaptation for MC-CDMA radio interface

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Association of hypoadiponectemia with smokeless/dipping tobacco use in young men

Background: Low levels of adiponectin, an adipocytokine with anti-diabetic, antiatherogenic and cardioprotective properties, is associated with increased risk of coronary disease in young men. Previous studies have demonstrated that smokeless tobacco is linked with a reduction of plasma adiponectin levels. However, the influence of smokeless tobacco (dipping tobacco) on plasma adiponectin levels still remains unknown. This study was conducted to assess the plasma adiponectin levels in young men who were using dipping tobacco. Methods: This was a community based study, which consisted of 186 young lean healthy males aged 20 to 35 years. Among these, 96 men were dipping tobacco users (BMI = 23.07 ± 2.68) and 90 were non-dipping tobacco users (BMI = 23.67 ± 1.46). Serum adiponectin levels were assessed by Enzyme Linked ImmunoSorbent Assay (ELISA). Results: A statistically significant difference in the mean adiponectin level between tobacco dipper and non-dipper groups was observed (p = 0.0001). A significant difference between the two groups was also observed in baseline parameters including triglyceride and random blood sugar levels (p < 0.05). However, no significant difference was observed between the two groups in other clinical parameters. Conclusions: Findings of this study suggest that dipping tobacco use was significantly associated with low level of adiponetin in community dwelling young males. This emphasizes the importance of developing community intervention to reduce the use of dipping tobacco, which will reduce the tobacco associated disease burden in the community and will improve public health

Visual Crowd Analysis: Open Research Problems

Over the last decade, there has been a remarkable surge in interest in automated crowd monitoring within the computer vision community. Modern deep-learning approaches have made it possible to develop fully-automated vision-based crowd-monitoring applications. However, despite the magnitude of the issue at hand, the significant technological advancements, and the consistent interest of the research community, there are still numerous challenges that need to be overcome. In this article, we delve into six major areas of visual crowd analysis, emphasizing the key developments in each of these areas. We outline the crucial unresolved issues that must be tackled in future works, in order to ensure that the field of automated crowd monitoring continues to progress and thrive. Several surveys related to this topic have been conducted in the past. Nonetheless, this article thoroughly examines and presents a more intuitive categorization of works, while also depicting the latest breakthroughs within the field, incorporating more recent studies carried out within the last few years in a concise manner. By carefully choosing prominent works with significant contributions in terms of novelty or performance gains, this paper presents a more comprehensive exposition of advancements in the current state-of-the-art.Comment: Accepted in AI Magazine published by Wiley Periodicals LLC on behalf of the Association for the Advancement of Artificial Intelligenc

Comparison of clonidine and dexmedetomidine as adjuvants for ropivacaine in ultrasound guided transversus abdominis plane block for post caesarean analgesia

Background: Transversus abdominis plane block is an important regional anaesthesia technique for postoperative analgesia after caesarean section. Addition of adjuvants to local anaesthetic in TAP block helps in improving the duration of analgesia. Objective of current study was to compare clonidine and dexmedetomidine as adjuvants to 0.2% ropivacaine in USG guided TAP block for duration of postoperative analgesia in caesarean section under spinal anaesthesia.Methods: A total of 75 pregnant patients belonging to ASA I-II scheduled for caesarean section were included and divided into three groups; Group I-0.2% Ropivacaine plus normal saline, Group II-0.2% Ropivacaine plus 50 mcg clonidine and Group III-0.2% ropivacaine plus 50 mcg dexmedetomidine. The patients were compared for duration of analgesia, total       number and amount of rescue analgesia utilized in 24        hours.Results: The mean duration of analgesia was found to be more (statistically significant p<0.05) and number as well as amount of rescue analgesic doses were reduced in group III as compared to group I and group II.Conclusions: Dexmedetomidine is a better alternative to clonidine as adjuvant for 0.2% ropivacaine in USG guided TAP block to extend the duration of postoperative analgesia and decreased 24-hour analgesic requirement in caesarean section

Hierarchical deep learning-based adaptive time-stepping scheme for multiscale simulations

Multiscale is a hallmark feature of complex nonlinear systems. While the simulation using the classical numerical methods is restricted by the local \textit{Taylor} series constraints, the multiscale techniques are often limited by finding heuristic closures. This study proposes a new method for simulating multiscale problems using deep neural networks. By leveraging the hierarchical learning of neural network time steppers, the method adapts time steps to approximate dynamical system flow maps across timescales. This approach achieves state-of-the-art performance in less computational time compared to fixed-step neural network solvers. The proposed method is demonstrated on several nonlinear dynamical systems, and source codes are provided for implementation. This method has the potential to benefit multiscale analysis of complex systems and encourage further investigation in this area

Comparison of Ketamine and Pentazocine with Fentanyl and Propofol combination for anaesthesia during laparoscopic tubal ligation

Background: Laparoscopic tubal ligation have advantages of minimally invasive surgical technique, without risk of major haemorrhage, early postoperative ambulation and alimentation, making it suitable for ambulatory surgery. The choice of aneasthesia for laparoscopic ligation hence should consider the anaesthetic agents with a rapid onset of action and fast recovery time, with minimal problems for intraoperative control of haemodynamic, airway and pain relief as well as take consideration of the safety, quality, efficacy, and utilization of resources available to the given situation.Methods: A total of 100 patients aged from 18 to 45 years who were scheduled to undergo laparoscopic tubal ligation  were divided into Group I-  Ketamine plus pentazocine group (n=50), Group II- Propofol plus fentanyl group (n=50) and studied  for the intraoperative parameters (hemodynamic and respiratory profile), recovery time, postoperative side effects and discharge time.Results: Intraoperatively MAP and HR were consistently higher in group I as compared to group II. Incidence of apnea and need for bag and mask ventilation was significantly more in Group II than in Group I as was the incidence of Bradycardia. Postoperative nausea and vomiting, psychomimetic effects were significantly more in Group I than in Group II. The time to reach modified PADSS ≥9 (discharge time) was significantly longer in group I (140.3±12.82 min than in group II 102.2±9.2 min), P<0.01.Conclusions: Combination of ketamine and pentazocine gives good anaesthetic conditions during procedure with less incidence of airway and haemodynamic complications intraoperatively but more incidence of postoperative side effects like nausea, vomiting, psycomimetic effects, and time to meet discharge criteria, compared to propofol plus fentanyl

Contegra valved conduit in the paediatric population: an exciting prospect for right ventricle to pulmonary artery reconstruction; experience and outcomes at Aga Khan University

Objective: The focus of this study is to share the experience and outcomes of Contegra graft implantation in the paediatric and adult population in Pakistan. Methods: Between May 2007 and July 2011, 16 patients, underwent implantation of a Contegra valved conduit. All operations were performed through a median sternotomy with cardiopulmonary bypass. Indications included: Pulmonary atresia with ventricular septal defect (n=11), Tetralogy of Fallot with absent Pulmonary Valve (PV) syndrome (n=2), double outlet right ventricle, transposition of great arteries and pulmonary stenosis (n=1), isolated aortic valve disease (n=1) and a pseudo-aneurysm with infective endocarditis (n=1).Conduit sizes varied between 16-22 mm. Results: The three in hospital deaths were unrelated to the Contegra valved conduit. One patient was lost to follow up. Of the 12 survivors, 10 are currently free from re-operation or complications related to the conduit while one needed distal pulmonary artery dilatation owing to critical stenosis and another had severe Valvular regurgitation. Echocardiographic evaluation of the Contegra valved conduit demonstrated no haemodynamically significant valve regurgitation in 10 patients. Conclusion: In this small review of 16 operations using the Contegra valved conduit for Right Venticular Outflow Tract (RVOT) reconstruction in the paediatric population, we observed good post operative results concerning conduit function. The Contegra conduit provides an excellent substitute to the homograft with satisfactory early and mid-term results though long term results are awaited in Pakista

Band Based Dynamic Link Adaptation for MC-CDMA Radio Interface

This paper studies adaptive power allocation among sub-carriers in MC-CDMA. Due to intrinsic nature of MC-CDMA; Carrier Based power allocation schemes cause MAI (Multiple Access Interference) enhancements, hence fail at higher system loads. We propose a Band Based Dynamic Link Adaptation (BBDLA) scheme that preserves orthogonality (among users) by spreading user’s signal only over a Band of adjacent N sub-carriers (N < Nsc 1 ) lying within coherence bandwidth (Bc) of the channel. Hence, it allows Band Based power allocation without causing any MAI. However, with only N orthogonal users supported on a particular Band, BBDLA essentially proposes a hybrid of FDMA with MC-CDMA where Bands and transmit powers are optimally assigned to users by Base Station (in accordance with their channel state). Optimum Band allocation for BBDLA is found to be computationally intractable hence a sub-optimal heuristic approach is proposed with equal power distribution among all assigned Bands for each user. Effect of Bc over choice of N is studied and BBDLA with suitably chosen N, is shown to outperform other published Carrier Based power allocation schemes while it maintain almost single user BER performance up to 62% of full system loadin