Results 71 to 80 of about 2,020,211 (266)

Distributed Kernel K-Means for Large Scale Clustering

, 2017
Clustering samples according to an effective metric and/or vector space representation is a challenging unsupervised learning task with a wide spectrum of applications.
Decherchi, Sergio, Ferrarotti, Marco Jacopo, Rocchia, Walter   +2 more
core   +1 more source

The Fate (Outcome) of Clinically Apparent Single Lesion and Oligofocal Nephroblastomatosis Treated According to SIOP/GPOH Protocols for Wilms Tumor

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background The management of clinically apparent single lesions or oligofocal nephroblastomatosis, a facultative precursor of nephroblastoma, remains debated. Methods We retrospectively analyzed 37 patients with clinically apparent single or oligofocal nephroblastomatosis (two to three lesions per kidney) among 2347 patients registered between
Nils Welter, Jens‐Peter Schenk, Jenny Wegert, Manfred Gessler, Leo Kager, Stefan Wagenpfeil, Marina Müller, Jean‐Michel Wolff, Joerg Fuchs, Steven W. Warmann, Clemens‐Magnus Meier, Jochen Hubertus, Christian Rübe, Christian Vokuhl, Patrick Melchior, Lena Tschirner, Norbert Graf, Rhoikos Furtwängler   +17 more
wiley   +1 more source

Using classification and K-means methods to predict breast cancer recurrence in gene expression data

Journal of Medical Signals and Sensors, 2022
Background: Breast cancer is a type of cancer that starts in the breast tissue and affects about 10% of women at different stages of their lives.
Mohammadreza Sehhati, Mohammad Amin Tabatabaiefar, Ali Haji Gholami, Mohammad Sattari   +3 more
doaj   +1 more source

k-Means [PDF]

, 2023
The k-means clustering algorithm (k-means for short) provides a method offinding structure in input examples. It is also called the Lloyd–Forgy algorithm as it was independently introduced by both Stuart Lloyd and Edward Forgy. k-means, like other algorithms you will study in this part of the book, is an unsupervised learning algorithm and, as such ...
openaire  

Inpatient Food Insecurity and Pediatric Hematology Oncology Hospitalization Outcomes

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Children with cancer and blood disorders are at risk for food insecurity (FI). We aimed to describe the association of inpatient food insecurity (IFI) and hospitalization outcomes among patients admitted to the pediatric hematology oncology service. Of 325 caregivers screened for IFI, 60 (18.6%) screened positive.
Joanna M. Robles, Greg Russell, Leila H. DeWitt, Kimberly Montez, Callie L. Brown   +4 more
wiley   +1 more source

Germline TP53 Mutations Causing Diamond–Blackfan Anemia: A French Report

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Diamond–Blackfan anemia is a rare congenital erythroblastopenia typically caused by mutations in ribosomal protein genes. Recently, gain‐of‐function mutations in TP53 have been identified as a novel cause of Diamond–Blackfan anemia. We report two French patients who both harbored a heterozygous TP53 deletion (NM_000546.5: c.1077delA; p ...
Rafael Moisan, Lydie Da Costa, Ludivine David Nguyen, Heloise Chosseler, Audrey Riquet, Benedicte Bruno, Melissa Barbati   +6 more
wiley   +1 more source

‘They Need to Hear You Say It’: Healthcare Professionals’ Perspectives on Barriers and Enablers to End‐of‐Life Discussions With Adolescents and Young Adults With Cancer

Pediatric Blood &Cancer, EarlyView.
ABSTRACT End‐of‐life conversations with adolescents and young adults (AYAs) with cancer rarely occur without the guidance of healthcare professionals. As a part of the ‘Difficult Discussions’ study, focused on palliative care and advance care planning discussions with AYAs with cancer, we investigated the factors that healthcare professionals identify ...
Justine Lee, Holly Evans, Claire E. Wakefield, Antoinette Anazodo, Richard J. Cohn, Brittany C. McGill, Elizabeth A. Lobb, Lori Wiener, Madeleine L. Juhrmann, Ursula M. Sansom‐Daly   +9 more
wiley   +1 more source

Global channel attention boosted active millimeter wave image object detection

Dianzi Jishu Yingyong
Due to the low discrimination between objects and background texture in active millimeter wave images and the need for security in real time, a global channel attention booster-based method for active millimeter wave image object detection is proposed ...
Jiang Tiantian, Ye Xueyi, Li Gang, Yang Menghao, Chen Huahua   +4 more
doaj   +1 more source

A Comparative Study of K-means Clustering Algorithms Using Euclidean and Manhattan Distance for Climate Data. [PDF]

المجلة العراقية للعلوم الاحصائية
The K-means clustering algorithms (Random, K-means++, Canopy, and Farthest First) are unsupervised machine learning techniques designed to group data points based on their similarities. The study examined the effects of clustering algorithms and distance
Bakhshan Hamad
doaj   +1 more source

K-means** - a fast and efficient K-means algorithms

International Journal of Intelligent Information and Database Systems, 2018
K-means often converges to a local optimum. In improved versions of K-means, k-means++ is well-known for achieving a rather optimum solution with its cluster initialisation strategy and high computational efficiency. Incremental K-means is recognised for its converging to the empirically global optimum but having a high complexity due to its stepping ...
Cuong Duc Nguyen, Trong Hai Duong
openaire   +1 more source