Indian Institute of Management Bangalore

About: Indian Institute of Management Bangalore is a education organization based out in Bengaluru, Karnataka, India. It is known for research contribution in the topics: Emerging markets & Context (language use). The organization has 491 authors who have published 1254 publications receiving 23853 citations. The organization is also known as: IIMB.

Prospectively-validated deep learning model for segmenting swallowing and chewing structures in CT

Abstract: Abstract Objective. Delineating swallowing and chewing structures aids in radiotherapy (RT) treatment planning to limit dysphagia, trismus, and speech dysfunction. We aim to develop an accurate and efficient method to automate this process. Approach. CT scans of 242 head and neck (H&N) cancer patients acquired from 2004 to 2009 at our institution were used to develop auto-segmentation models for the masseters, medial pterygoids, larynx, and pharyngeal constrictor muscle using DeepLabV3+. A cascaded framework was used, wherein models were trained sequentially to spatially constrain each structure group based on prior segmentations. Additionally, an ensemble of models, combining contextual information from axial, coronal, and sagittal views was used to improve segmentation accuracy. Prospective evaluation was conducted by measuring the amount of manual editing required in 91 H&N CT scans acquired February-May 2021. Main results . Medians and inter-quartile ranges of Dice similarity coefficients (DSC) computed on the retrospective testing set ( N = 24) were 0.87 (0.85–0.89) for the masseters, 0.80 (0.79–0.81) for the medial pterygoids, 0.81 (0.79–0.84) for the larynx, and 0.69 (0.67–0.71) for the constrictor. Auto-segmentations, when compared to two sets of manual segmentations in 10 randomly selected scans, showed better agreement (DSC) with each observer than inter-observer DSC. Prospective analysis showed most manual modifications needed for clinical use were minor, suggesting auto-contouring could increase clinical efficiency. Trained segmentation models are available for research use upon request via https://github.com/cerr/CERR/wiki/Auto-Segmentation-models . Significance. We developed deep learning-based auto-segmentation models for swallowing and chewing structures in CT and demonstrated its potential for use in treatment planning to limit complications post-RT. To the best of our knowledge, this is the only prospectively-validated deep learning-based model for segmenting chewing and swallowing structures in CT. Segmentation models have been made open-source to facilitate reproducibility and multi-institutional research.

Consumer behaviour, customer satisfaction vis-a-vis brand performance: an empirical study of dairy food supply chain in India

Abstract: Quantifying customer satisfaction in any manufacturing or service supply chain is extremely important to know the end-user preferences. The higher the customer satisfaction, the higher is the sales, which in turn leads to better supply chain performance. In the current study customer satisfaction is measured quantitatively from a dairy food supply chain perspective in India. The data collected from the customers have been subjected to a rigorous analysis giving due weightage to the sampling and reliability of the instrument used for the study. From large number of indicators, factors have been drawn by using factor analysis and customer satisfaction index has been calculated thereto. The empirical findings are expected to add value to the concept where products are highly perishable and need conditioned transportation at every stage.

Perception of Entrepreneurial Ecosystem: Testing the Actor–Observer Bias:

Abstract: Entrepreneurial ecosystem is the interacting socio-economic environment that facilitates entrepreneurs to start and develop their enterprises. A vibrant and supportive entrepreneurial ecosystem is ...

Non-GAAP earnings: international overview and suggestions for future research

Abstract: Purpose The purpose of this paper is to synthesize insights from existing research on the disclosure of non-generally accepted accounting principles (GAAP) earnings, from an international point of view, and to suggest several avenues for future research in this area. Design/methodology/approach In conjunction with the analysis of existing research, the paper examines how different regulators and accounting standard setters have approached the topic of non-GAAP earnings disclosure. Findings The paper shows how non-GAAP earnings have been found to be more informative than GAAP earnings in several scenarios (countries where non-GAAP disclosures are compulsory, countries where these disclosures are voluntary but regulated and countries where they are not regulated). However, in certain circumstances, these disclosures may also mislead investors. Corporate governance mechanisms can curb managers’ opportunistic use of these measures. Originality/value The paper provides the growing number of academic researchers in this emerging area with a foundation and agenda upon which they can build their research.

Report from a symposium on catalyzing primary and secondary prevention of cancer in India

Abstract: Purpose Oral, breast, and cervical cancers are amenable to early detection and account for a third of India’s cancer burden. We convened a symposium of diverse stakeholders to identify gaps in evidence, policy, and advocacy for the primary and secondary prevention of these cancers and recommendations to accelerate these efforts.