Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph

While conversing with chatbots, humans typically tend to ask many questions, a significant portion of which can be answered by referring to large-scale knowledge graphs (KG). While Question Answering (QA) and dialog systems have been studied independently, there is a need to study them closely to evaluate such real-world scenarios faced by bots involving both these tasks. Towards this end, we introduce the task of Complex Sequential QA which combines the two tasks of (i) answering factual questions through complex inferencing over a realistic-sized KG of millions of entities, and (ii) learning to converse through a series of coherently linked QA pairs. Through a labor intensive semi-automatic process, involving in-house and crowdsourced workers, we created a dataset containing around 200K dialogs with a total of 1.6M turns. Further, unlike existing large scale QA datasets which contain simple questions that can be answered from a single tuple, the questions in our dialogs require a larger subgraph of the KG. Specifically, our dataset has questions which require logical, quantitative, and comparative reasoning as well as their combinations. This calls for models which can: (i) parse complex natural language questions, (ii) use conversation context to resolve coreferences and ellipsis in utterances, (iii) ask for clarifications for ambiguous queries, and finally (iv) retrieve relevant subgraphs of the KG to answer such questions. However, our experiments with a combination of state of the art dialog and QA models show that they clearly do not achieve the above objectives and are inadequate for dealing with such complex real world settings. We believe that this new dataset coupled with the limitations of existing models as reported in this paper should encourage further research in Complex Sequential QA.Comment: Accepted in AAAI'1

Tear biomarkers for keratoconus

Keratoconus is a progressive corneal thinning, ectatic condition, which affects vision. Recent advances in corneal topography measurements has helped advance proper diagnosis of this condition and increased research and clinical interests in the disease etiopathogenesis. Considerable progress has been achieved in understanding the progression of the disease and tear fluid has played a major role in the progress. This review discusses the importance of tear fluid as a source of biomarker for keratoconus and how advances in technology have helped map the complexity of tears and thereby molecular readouts of the disease. Expanding knowledge of the tear proteome, lipidome and metabolome opened up new avenues to study keratoconus and to identify probable prognostic or diagnostic biomarkers for the disease. A multidimensional approach of analyzing tear fluid of patients layering on proteomics, lipidomics and metabolomics is necessary in effectively decoding keratoconus and thereby identifying targets for its treatment

Bupivacaine 0.5% vs. levobupivacaine 0.5% for epidural anaesthesia for caesarean section: a comparative study

Background: Levobupivacaine has been purported to be as efficacious as Bupivacaine for epidural anaesthesia in recent literature.Methods: With the intent to study the same in caesarean section cases in our set up, we observed various intra- and post-operative variables in two groups (Levobupivacaine and Bupivacaine) of 60 healthy parturients. Sixty parturients for elective caesarean section were allocated randomly to receive epidural block with 10-20 ml of either 0.5% Levobupivacaine with Fentanyl 25µg or 0.5% Bupivacaine with Fentanyl 25µg to reach T6 level.Results: Mean total volume in Bupivacaine group was 15.23ml and in Levobupivacaine group was 12.76 ml. The difference was statistically significant. There was significant difference between the groups in the sensory block. The onset of analgesia was earlier in Levobupivacaine group. Mean time was 6.20 minutes in Bupivacaine group and 4.36 minutes in Levobupivacaine group. The duration of motor block was significantly short in Levobupivacaine group. Mean Time for recovery from motor block in Bupivacaine group was 2.5 hours and in Levobupivacaine group 1.5 hours. Mean time to achieve T6 height was earlier in Levobupivacaine group i.e. 16.46 minutes in Bupivacaine group and 13.26 minutes in Levobupivacaine group. Duration of postoperative analgesia was similar. There was no significant difference in neonatal outcome.Conclusions: Levobupivacaine was found to fare better than Bupivacaine in the studied intra and post-operative parameters and is hence recommended over racemic Bupivacaine for epidural block in patients undergoing elective cesarean section

Identifying Prognostic Groups Using Machine Learning Tools in Patients Undergoing Chemoradiation for Inoperable Locally Advanced Nonsmall Cell Lung Carcinoma

Introduction Unresectable stage III nonsmall cell lung cancer (NSCLC) continues to have dismal 5-year overall survival (OS) rate. However, a subset of the patients treated with chemoradiation show significantly better outcome. Prediction of treatment outcome can be improved by utilizing machine learning tools, such as cluster analysis (CA), and is capable of identifying complex interactions among many variables. We have utilized CA to identify a cluster with good prognosis within stage III NSCLC. Materials and Methods Retrospective analysis of treatment outcomes was done for 92 patients who underwent chemoradiation for inoperable locally advanced NSCLC from 2012 to 2018. Using various patient- and treatment-related variables, an exploratory factor analysis was performed to extract factors with eigenvalue > 1. An appropriate number of homogeneous groups were identified using agglomerative hierarchical cluster analysis. Further K-mean cluster analysis was applied to classify each patient into their homogeneous clusters. The newly formed cluster variable was used as an independent variable to estimate survival over time using Kaplan–Meier method. Results With a median follow-up of 18 months, median OS was 14 months. Using CA, three prognostic clusters were obtained. Cluster 2 with 36 patients had a median OS of 36 months, whereas Cluster 1 with 34 patients had a median OS of 20 months (p = 0.004). Conclusion A cluster could thus be identified with a relatively good prognosis within stage III NSCLC. Using CA, we have attempted to create a model which may provide more specific prognostic information in addition to that provided by tumor node metastasis-based models

Plan quality assessment of modern radiotherapy delivery techniques in left-sided breast cancer: an analysis stratified by target delineation guidelines

Objective: This study compares planning techniques stratified by consensus delineation guidelines in patients undergoing whole-breast radiotherapy based on an objective plan quality assessment scale. Methods: 10 patients with left-sided breast cancer were randomly selected, and target delineation for intact breast was performed using Tangent (RTOG 0413), ESTRO, and RTOG guidelines. Consensus Plan Quality Metric (PQM) scoring was defined and communicated to the physicist before commencing treatment planning. Field-in-field IMRT (FiF), inverse IMRT (IMRT) and volumetric modulated arc therapy (VMAT) plans were created for each delineation. Statistical analyses utilised a two-way repeated measures analysis of variance, after applying a Bonferroni correction. Results: Total PQM score of plans for Tangent and ESTRO were comparable for FiF and IMRT techniques (FiF vs IMRT for Tangent, p = 0.637; FiF vs IMRT for ESTRO, p = 0.304), and were also significantly higher compared to VMAT. Total PQM score of plans for RTOG revealed that IMRT planning achieved a significantly higher score compared to both FiF and VMAT (IMRT vs FiF, p &lt; 0.001; IMRT vs VMAT, p &lt; 0.001). Conclusions: Total PQM scores were equivalent for FiF and IMRT for both Tangent and ESTRO delineations, whereas IMRT was best suited for RTOG delineation. Advances in knowledge: FiF and IMRT planning techniques are best suited for ESTRO or Tangent delineations. IMRT also yields better results with RTOG delineation. </jats:sec

"More than just a medical student”: a mixed methods exploration of a structured volunteering programme for undergraduate medical students

Background As a result of the COVID-19 pandemic Imperial College School of Medicine developed a structured volunteering programme involving 398 medical students, across eight teaching hospitals. This case study aims to illuminate the experiences of volunteers, mechanisms of learning and draw lessons for future emergencies and curriculum improvements. Methods Using an illuminative approach to evaluation we invited all volunteers and supervisors to complete a mixed-methods survey. This gathered nominal demographic information and qualitative data related to motivations, experiences, insights into learning, processual and contextual factors. Qualitative responses were coded, thematically organised, and categorised into an overarching framework. Mann-Whitney U tests determined whether volunteers’ overall rating of the experience varied according to demographic features and modulating factors. Spearman’s rank correlation assessed the relationship between aspects of induction and supervision, and overall volunteering rating. Follow up interviews were carried out with students to check back findings and co-create conclusions. Results Modulating factors identified through thematic analysis include altruistic motivation, engaged induction and supervision, feeling valued, having responsibility and freedom from the formal curriculum. Statistically significant positive correlations are identified between volunteers overall rating and being a year 1 or 2 student, ability to discuss role and ask questions during induction, being male, and having regular meetings and role support from supervisors. Qualitatively reported impacts include improved wellbeing, valuable contribution to service and transformative learning. Transformative learning effects included reframing of role within the multidisciplinary team, view of effective learning and view of themselves as competent clinicians. The number of weeks, number of shifts per week, and the role the volunteers performed, did not significantly impact experiences. Conclusions While acknowledging the uniqueness of the situation presented by the first wave COVID-19, we suggest the features of a successful service-learning programme include: a learner-centred induction, engaged and appreciative supervisors, and the entrustment of students with meaningful work with reciprocal benefits to services. Programmes in similar settings may find that 1) volunteering is best appreciated in years 1 or 2, 2) students with altruistic motivations and meaningful work may flourish without formal outcomes and assessments, and 3) that female volunteers may experience emergency learning differently to men

Intuitive evaluation of contemporary management strategies in thymoma — the largest Indian experience

Background: The aim was perusal of the treatment strategies, clinical outcomes and factors impacting these outcomes in thymoma. Materials and methods: A total of 119 patients diagnosed and treated cases of thymoma, at our hospital, were taken for analysis. Thirty-one patients were excluded due to inadequate medical records. Descriptive statistics were used to report demographic and clinical characteristics. Time period between diagnosis and death was defined as overall survival (OS). Multivariate analysis (MVA), using cox regression modelling, was done by including clinicopathological factors in a bid to identify prognostic factors influencing OS. SPSS version 26 was used for statistical analysis. Results: The mean age of the patients was 52.17 years and 39 (44.3%), 19 (21.6%), 17 (1.3%) and 13 (4.8%) patients presented with Masaoka stage II, IV, III and I, respectively. Surgery was done in 64 (72.7%) of the patients as a part of the treatment strategy. Radiotherapy was administered to a total of 57 patients with a median dose of 50.4 Gy. Early Masaoka stage at presentation and use of surgery in the treatment plan were statistically significant prognostic factors for a better overall survival on multivariate analysis. Conclusion: Judicious use of radiotherapy and chemotherapy in locally advanced cases may render them resectable. In a bid to gain good survival rates, aggressive multimodality treatment should be offered to the patients