Results 61 to 70 of about 4,859,475 (319)

Plasmodium falciparum gametogenesis essential protein 1 (GEP1) is a transmission‐blocking target

FEBS Letters, EarlyView.
This study shows Plasmodium falciparum GEP1 is vital for activating sexual stages of malarial parasites even independently of a mosquito factor. Knockout parasites completely fail gamete formation even when a phosphodiesterase inhibitor is added. Two single‐nucleotide polymorphisms (V241L and S263P) are found in 12%–20% of field samples.
Frederik Huppertz, Milagros Siebeck Caturelli, Lina S. Lehmann, Florian Kurth, Alexander G. Maier, Kai Matuschewski   +5 more
wiley   +1 more source

Data‐driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Molecular Oncology, EarlyView.
This study investigates gene expression differences between two major pediatric acute lymphoblastic leukemia (ALL) subtypes, B‐cell precursor ALL, and T‐cell ALL, using a data‐driven approach consisting of biostatistics and machine learning methods. Following analysis of a discovery dataset, we find a set of 14 expression markers differentiating the ...
Mona Nourbakhsh, Nikola Tom, Anna Schrøder Lassen, Helene Brasch Lind Petersen, Ulrik Kristoffer Stoltze, Karin Wadt, Kjeld Schmiegelow, Matteo Tiberti, Elena Papaleo   +8 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

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

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

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

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

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

Entropy-Based Greedy Algorithm for Decision Trees Using Hypotheses

Entropy, 2021
In this paper, we consider decision trees that use both conventional queries based on one attribute each and queries based on hypotheses of values of all attributes. Such decision trees are similar to those studied in exact learning, where membership and
Mohammad Azad, Igor Chikalov, Shahid Hussain, Mikhail Moshkov   +3 more
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