Results 111 to 120 of about 30,987,372 (386)

IntervalSketch:Approximate Statistical Method for Interval Items in Data Stream [PDF]

Jisuanji kexue
The proportion of streaming databases is gradually increasing,and extracting the required information in the data streams of streaming databases is an important task.In this paper,we study interval items which refer to pairs of elements arriving with a ...
CHEN Xinyang, CHEN Hanze, ZHOU Jiasheng, HUANG Jiaqing, YU Jiashuo, ZHU Longlong, ZHANG Dong
doaj   +1 more source

Time interval after various types of gastrectomy until metachronous multiple gastric cancer: Analysis of data from a nationwide Japanese survey

, 2021
Koshi Kumagai, Sang‐Woong Lee, Masaichi Ohira, Masaki Aizawa, Satoshi Kamiya, Takaomi Takahata, Makoto Toda, Haruhiko Cho, Masazumi Takahashi, Takeshi Kubota, Shinichi Kinami, Takeo Kosaka   +11 more
openalex   +2 more sources

Weibull distribution based on maximum likelihood with interval inspection data [PDF]

The two Weibull parameters based upon the method of maximum likelihood are determined. The test data used were failures observed at inspection intervals.
Rheinfurth, M. H.
core   +1 more source

Phenotypic and genotypic characterization of single circulating tumor cells in the follow‐up of high‐grade serous ovarian cancer

Molecular Oncology, EarlyView.
Single circulating tumor cells (sCTCs) from high‐grade serous ovarian cancer patients were enriched, imaged, and genomically profiled using WGA and NGS at different time points during treatment. sCTCs revealed enrichment of alterations in Chromosomes 2, 7, and 12 as well as persistent or emerging oncogenic CNAs, supporting sCTC identity.
Carolin Salmon, Rui P. L. Neves, Nikolas H. Stoecklein, Sven‐Thorsten Liffers, Jens Siveke, Jan D. Kuhlmann, Pauline Wimberger, Paul Buderath, Rainer Kimmig, Sabine Kasimir‐Bauer   +9 more
wiley   +1 more source

Data envelopment analysis with imprecise data: Fuzzy and interval modeling approaches

Results in Control and Optimization
Data Envelopment Analysis with inaccurate data poses a significant challenge in data science and analytics due to the inherent uncertainties and discrepancies present in real-world data.
Hassan Mishmast Nehi, Faranak Hosseinzadeh Saljooghi, Amir Rahimi, Laxmi Rathour, Lakshmi Narayan Mishra, Vishnu Narayan Mishra   +5 more
doaj   +1 more source

Combining antibody conjugates with cytotoxic and immune‐stimulating payloads maximizes anti‐cancer activity

Molecular Oncology, EarlyView.
Methods to improve antibody–drug conjugate (ADC) treatment durability in cancer therapy are needed. We utilized ADCs and immune‐stimulating antibody conjugates (ISACs), which are made from two non‐competitive antibodies, to enhance the entry of toxic payloads into cancer cells and deliver immunostimulatory agents into immune cells.
Tiexin Wang, Dong Jun Koo, Peter M. Tessier, Greg M. Thurber   +3 more
wiley   +1 more source

On solving interval data based assignment problem under fuzzy environment

, 2021

openalex   +1 more source

A Quantile Variant of the EM Algorithm and Its Applications to Parameter Estimation with Interval Data

, 2018
The expectation-maximization (EM) algorithm is a powerful computational technique for finding the maximum likelihood estimates for parametric models when the data are not fully observed.
Chanseok Park, Cox DR, Dempster AP, Elsayed EA., Govindarajulu Z., Leemis LM., Press WH, Robert CP, Sun J.   +8 more
core   +1 more source

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

Comparing Survival Functions with Doubly Interval-Censored Data: An Application to Diabetes Surveyed by Korean Cancer Prevention Study [PDF]

, 2009
Sun Ha Jee, Chung Mo Nam, Jinheum Kim
openalex   +1 more source