Results 51 to 60 of about 4,926,046 (277)

Machine learning for identifying liver and pancreas cancers through comprehensive serum glycopeptide spectra analysis: a case‐control study

Molecular Oncology, EarlyView.
This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima, Yuko Takami, Ken Kawabe, Kazuhiro Tanabe, Chihiro Hayashi, Mikio Mikami, Tetsuya Kusumoto   +6 more
wiley   +1 more source

Characterizing the salivary RNA landscape to identify potential diagnostic, prognostic, and follow‐up biomarkers for breast cancer

Molecular Oncology, EarlyView.
This study explores salivary RNA for breast cancer (BC) diagnosis, prognosis, and follow‐up. High‐throughput RNA sequencing identified distinct salivary RNA signatures, including novel transcripts, that differentiate BC from healthy controls, characterize histological and molecular subtypes, and indicate lymph node involvement.
Nicholas Rajan, Irina Primac, Emre Etlioglu, Laurens Debruyne, Ann Janssen, Magy Sallam, Kevin Tabury, Roel Quintens, Wiebren Tjalma, Mohammed Abderrafi Benotmane   +9 more
wiley   +1 more source

Complexity of Deterministic and Strongly Nondeterministic Decision Trees for Decision Tables From Closed Classes

IEEE Access
This paper investigates classes of decision tables (DTs) with 0-1-decisions that are closed under the removal of attributes (columns) and changes to the assigned decisions to rows.
Azimkhon Ostonov, Mikhail Moshkov
doaj   +1 more source

Gut microbiota diversity is prognostic in metastatic hormone receptor‐positive breast cancer patients receiving chemotherapy and immunotherapy

Molecular Oncology, EarlyView.
In this exploratory study, we investigated the relationship between the gut microbiota and outcome in patients with metastatic hormone receptor‐positive breast cancer, treated in a randomized clinical trial with chemotherapy alone or chemotherapy in combination with immune checkpoint blockade.
Andreas Ullern, Kristian Holm, Nikolai Kragøe Andresen, Andreas Hagen Røssevold, Corinna Bang, Bjørn Naume, Johannes R. Hov, Jon Amund Kyte   +7 more
wiley   +1 more source

Method of decision tree applied in adopting the decision for promoting a company

Annals of Spiru Haret University Economic Series, 2015
The decision can be defined as the way chosen from several possible to achieve an objective. An important role in the functioning of the decisional-informational system is held by the decision-making methods.
Cezarina Adina TOFAN
doaj   +1 more source

Assessment of potential human health risks in aquatic products based on the heavy metal hazard decision tree [PDF]

, 2021
Hao‐Hsiang Ku, Pinpin Lin, Min‐Pei Ling   +2 more
openalex   +1 more source

Private Evaluation of Decision Trees using Sublinear Cost

Proceedings on Privacy Enhancing Technologies, 2019
Decision trees are widespread machine learning models used for data classification and have many applications in areas such as healthcare, remote diagnostics, spam filtering, etc.
Anselme Tueno, F. Kerschbaum, S. Katzenbeisser   +2 more
semanticscholar   +1 more source

Patient‐specific pharmacogenomics demonstrates xCT as predictive therapeutic target in colon cancer with possible implications in tumor connectivity

Molecular Oncology, EarlyView.
This study integrates transcriptomic profiling of matched tumor and healthy tissues from 32 colorectal cancer patients with functional validation in patient‐derived organoids, revealing dysregulated metabolic programs driven by overexpressed xCT (SLC7A11) and SLC3A2, identifying an oncogenic cystine/glutamate transporter signature linked to ...
Marco Strecker, Keren Zohar, Martin Böttcher, Thomas Wartmann, Henry Freudenstein, Maximilian Doelling, Mihailo Andric, Wenjie Shi, Or Kakhlon, Katrin Hippe, Beatrix Jahnke, Dimitrios Mougiakakos, Franziska Baenke, Daniel Stange, Roland S. Croner, Michal Linial, Ulf D. Kahlert   +16 more
wiley   +1 more source

A case study for assessing the utility of a decision tree based learning algorithm in mental health inpatient care quality management

European Psychiatry, 2022
Introduction There is limited knowledge about the potential role of machine learning (ML) in quality improvement of psychiatric care. Objectives Our case study was to determine whether ML decision trees used on patient databases are suitable for ...
R. Wernigg, M. Wernigg
doaj   +1 more source

End-to-End Learning of Decision Trees and Forests

International Journal of Computer Vision, 2019
Conventional decision trees have a number of favorable properties, including a small computational footprint, interpretability, and the ability to learn from little training data.
Thomas M. Hehn, Julian F. P. Kooij, F. Hamprecht   +2 more
semanticscholar   +1 more source