Development of a Corresponding-State “Association Enthalpy” Function for Use in the Prediction of Coal Liquid Enthalpies
R Sharma, A Baid, IS Jayaram - Industrial & engineering chemistry …, 1999 - ACS Publications
A simple corresponding-state “association enthalpy” function in terms of reduced
temperature, reduced pressure, and an “association factor” which accounts for the effect of “association…
temperature, reduced pressure, and an “association factor” which accounts for the effect of “association…
Private Equity Decision Making Using a Risk-Weighted Optimal Decision-Making Paradigm and Neural Networks
A Sugathan, A Baid - The Journal of Private Equity, 2013 - JSTOR
Private equity (PE) fund managers constantly face the problem of having an adequate
selection of firms to invest in. Optimal investment decisions are of high importance to PE funds …
selection of firms to invest in. Optimal investment decisions are of high importance to PE funds …
To develop a system for maintaining optimum level of inventories of locally procured components subject to varying demand
N Katoch, A Baid - 2012 - repository.iimb.ac.in
Nokia is one of the largest mobile phone manufacturers in the world. The company manufactures
handsets in 2 categories: mobile phones and smart devices. There are 4 factories for …
handsets in 2 categories: mobile phones and smart devices. There are 4 factories for …
The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification
U Baid, S Ghodasara, S Mohan, M Bilello… - arXiv preprint arXiv …, 2021 - arxiv.org
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the
Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR…
Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR…
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
Gliomas are the most common primary brain malignancies, with different degrees of
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie, …
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie, …
Deep learning radiomics algorithm for gliomas (drag) model: a novel approach using 3d unet based deep convolutional neural network for predicting survival in …
Automated segmentation of brain tumors in multi-channel Magnetic Resonance Image (MRI)
is a challenging task. Heterogeneous appearance of brain tumors in MRI poses critical …
is a challenging task. Heterogeneous appearance of brain tumors in MRI poses critical …
Papers Abstracts
Aim: Segmentation of brain tumors from multimodal magnetic resonance (MR) imaging remains
a challenge, and deep learning has a potential role in diagnosis, prognosis, and survival …
a challenge, and deep learning has a potential role in diagnosis, prognosis, and survival …
[HTML][HTML] Overall survival prediction in glioblastoma with radiomic features using machine learning
Glioblastoma is a WHO grade IV brain tumor, which leads to poor overall survival (OS) of
patients. For precise surgical and treatment planning, OS prediction of glioblastoma (GBM) …
patients. For precise surgical and treatment planning, OS prediction of glioblastoma (GBM) …
[HTML][HTML] A novel approach for fully automatic intra-tumor segmentation with 3D U-Net architecture for gliomas
Purpose: Gliomas are the most common primary brain malignancies, with varying degrees
of aggressiveness and prognosis. Understanding of tumor biology and intra-tumor …
of aggressiveness and prognosis. Understanding of tumor biology and intra-tumor …
The federated tumor segmentation (fets) challenge
This manuscript describes the first challenge on Federated Learning, namely the Federated
Tumor Segmentation (FeTS) challenge 2021. International challenges have become the …
Tumor Segmentation (FeTS) challenge 2021. International challenges have become the …