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Computational prediction model
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The presence of heterogeneity is a significant attribute within the context of ovarian cancer. This study aimed to assess the predictive accuracy of models utilizing quantitative 18F-FDG PET/CT derived inter-tumor heterogeneity metrics in determining progression-free survival (PFS) and overall survival (OS) in patients diagnosed with high-grade serous ovarian cancer (HGSOC).
13p
vishanshan
27-06-2024
2
1
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Chemoradiotherapy is a critical treatment for patients with locally advanced and unresectable nonsmall cell lung cancer (NSCLC), and it is essential to identify high-risk patients as early as possible owing to the high incidence of radiation pneumonitis (RP). This study aimed to investigate the value of computed tomography (CT)-based radiomics combined with genomics in analyzing the risk of grade≥2 RP in unresectable stage III NSCLC.
10p
vishanshan
27-06-2024
1
1
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Although radical surgical resection is the most effective treatment for hepatocellular carcinoma (HCC), the high rate of postoperative recurrence remains a major challenge, especially in patients with alpha-fetoprotein (AFP)-negative HCC who lack effective biomarkers for postoperative recurrence surveillance. In this study, we propose to develop a radiomics model based on preoperative CECT to predict the risk of early recurrence after surgery in AFP-negative HCC.
12p
vikoch
27-06-2024
1
1
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The risk category of gastric gastrointestinal stromal tumors (GISTs) are closely related to the surgical method, the scope of resection, and the need for preoperative chemotherapy. We aimed to develop and validate convolutional neural network (CNN) models based on preoperative venous-phase CT images to predict the risk category of gastric GISTs.
10p
vikoch
27-06-2024
2
1
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This present study aimed to develop and validate radiomics models based on pretreatment 18Fluorine-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)- computed tomography (CT) images to accurately predict the prognosis in patients.
14p
vikoch
27-06-2024
1
1
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Identifying lymph node metastasis areas during surgery for early invasive lung adenocarcinoma remains challenging. The aim of this study was to develop a nomogram mathematical model before the end of surgery for predicting lymph node metastasis in patients with early invasive lung adenocarcinoma.
24p
vikoch
27-06-2024
1
1
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Ebook "Systems medicine" guides readers through the field of systems medicine by defining the terminology, and describing how established computational methods form bioinformatics and systems biology can be taken forward to an integrative systems medicine approach. Chapters provide an outlook on the role that systems medicine may or should play in various medical fields, and describe different facets of the systems medicine approach in action.
492p
dongmelo
27-05-2024
6
2
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This study revealed that the major contributing descriptors of 2D QSAR studies are DeltaEpsilonB and DeltaPsiA and 3D QSAR model proves the steric as well as electrostatic effects determine the binding affinity for the drug development. The results of the current computational studies are useful for further designing novel chemical entities of anti-microbial agent.
19p
dianmotminh02
03-05-2024
5
2
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Ebook "Uncertainty in biology: A computational modeling approach" wants to address four main issues related to the building and validation of computational models of biomedical processes: (1) Modeling establishment under uncertainty; (2) Model selection and parameter fitting; (3) Sensitivity analysis and model adaptation; (4) Model predictions under uncertainty in each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples.
471p
ladongphongthanh1008
22-04-2024
5
2
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Ebook "Control and prediction of solid-state of pharmaceuticals: Experimental and computational approaches" investigates a range of experimental and computational approaches for the discovery of solid forms. Furthermore, we gain, as readers, a better understanding of the key factors underpinning solid-structure and diversity. A major part of this thesis highlights experimental work carried out on two structurally very similar compounds.
267p
tudohanhtau1006
29-03-2024
4
1
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Multi-omics data are good resources for prognosis and survival prediction; however, these are difficult to integrate computationally. We introduce DeepProg, a novel ensemble framework of deep-learning and machine-learning approaches that robustly predicts patient survival subtypes using multi-omics data.
15p
vibransone
28-03-2024
6
2
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Ebook "Introduction to computational mass transfer: With applications to chemical engineering" offers an easy-to-understand introduction to the computational mass transfer (CMT) method. On the basis of the contents of the first edition, this new edition is characterized by the following additional materials. It describes the successful application of this method to the simulation of the mass transfer process in a fluidized bed, as well as recent investigations and computing methods for predictions for the multi-component mass transfer process.
343p
tudohanhtau1006
29-03-2024
3
1
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Ebook "Protein modelling" detailed description of cutting-edge computational methods applied to protein modeling as well as specific applications are presented. Chapters include: the application of Car-Parrinello techniques to enzyme mechanisms, the outline and application of QM/MM methods, polarizable force fields, recent methods of ligand docking, molecular dynamics related to NMR spectroscopy, computer optimization of absorption, distribution, metabolism and excretion extended by toxicity for drugs, enzyme design and bioinformatics applied to protein structure prediction.
332p
tudohanhtau1006
29-03-2024
2
1
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Ebook "Computational fluid dynamics applications in food processing" has been applied extensively to great benefit in the food processing sector.
92p
coduathanh1122
27-03-2024
4
1
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Ebook "Computational methods for protein structure prediction and modeling - Volume 1: Basic characterization" is an attempt to fill this gap by providing systematic expositions of the computational methods for all major aspects of protein structure analysis, prediction, and modeling. We have designed the chapters to address comprehensively the main topics of the field. In addition, chapters have been connected seamlessly through a systematic design of the overall structure of the book.
407p
cotieubac1004
15-03-2024
1
0
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Part 1 book "Applied chemistry and chemical engineering (Vol 1: Mathematical and analytical techniques)" includes content: Digraphs, graphs, and thermodynamics equations; usefulness and limits of predictive relationships; computational model for byproduct of wastewater treatment; complex calculation of a critical path of motion of a corpuscle taking into account a regime and design of the apparatus; the modern approach to modeling and calculation of efficiency of process of a gas cleaning;... and other contents.
157p
muasambanhan08
01-03-2024
2
1
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Ebook "Theory of charge transport in carbon electronic materials" has been an issue of intensive interests and debates for over 50 years, not only because of the applications in printing electronics, but also because of the great challenges in understanding the electronic processes in complex systems. With the fast developments of both electronic structure theory and the computational technology, the dream of predicting the charge mobility is now gradually becoming a reality.
96p
nhanphanguyet
28-01-2024
5
2
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Ebook "Computational methods for GPCR drug discovery" looks at modern computational strategies and techniques used in GPCR drug discovery including structure and ligand-based approaches and cheminformatics.
437p
lamquandat
28-12-2023
6
2
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Bladder cancer (BLCA) is the ninth most common cancer globally, as well as the fourth most common cancer in men, with an incidence of 7%. However, few effective prognostic biomarkers or models of BLCA are available at present.
19p
vileonardodavinci
23-12-2023
5
2
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Preoperative prediction of pancreatic cystic neoplasm (PCN) differentiation has significant value for the implementation of personalized diagnosis and treatment plans. This study aimed to build radiomics deep learning (DL) models using computed tomography (CT) data for the preoperative differential diagnosis of common cystic tumors of the pancreas.
10p
vileonardodavinci
23-12-2023
6
3
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