Results 221 to 230 of about 693,025 (273)

Analyzing Generative AI and Machine Learning in Auto-Assessing Schizophrenia's Negative Symptoms. [PDF]

Schizophr Bull
Liu CM, Chan YH, Ho MY, Liu CC, Lu MH, Liao YA, Hsieh MH, Tseng YJ.   +7 more
europepmc   +1 more source

Advanced Materials for Biologics Delivery to Brain Tumors

Advanced Materials, EarlyView.
Material innovation is central to unlocking the therapeutic potential of biologics against many central nervous system diseases, including brain cancer. By engineering carriers with controlled transport, targeting, and release properties, advanced materials can overcome the blood–brain barrier and tumor microenvironment, improving the delivery of ...
Yuran Feng, Yuxue Cao, Maria Kavallaris, Taskeen Janjua, Amirali Popat   +4 more
wiley   +1 more source

XAI-Driven Intrusion Detection for Internet of Things Networks. [PDF]

Sensors (Basel)
Alqahtani A, Alakeel F, Abuhaimed L.
europepmc   +1 more source

Explainable deep learning for healthcare workforce attrition: a methodological study on the Watson healthcare synthetic benchmark. [PDF]

Front Public Health
Yin D, Lu X, Mei T.
europepmc   +1 more source

AER-DCWGAN: Adversarial Encoder-Regularized Dual-Conditional Wasserstein GAN for Imbalanced Network Intrusion Detection. [PDF]

Sensors (Basel)
Wang M, Yang Y, Gao M, Yuan J.
europepmc   +1 more source

Artificial intelligence techniques for classification of Alzheimer's disease using neuroimaging data: a review. [PDF]

Front Artif Intell
Nibila Y, Sivagami M.
europepmc   +1 more source

Sequence-based prediction of drug-target binding using machine learning, deep learning and ensemble models without 3D structural information. [PDF]

Sci Rep
Çevik N, Çevik T, Gürhanlı A.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Handling imbalance in hierarchical classification problems using local classifiers approaches

Data Mining and Knowledge Discovery, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yandre Costa, Carlos Silla, Rodolfo Miranda Pereira   +2 more
exaly   +2 more sources

Handling Concept Drifts Using Dynamic Selection of Classifiers

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI), 2016
This work describes the Dynse framework, which uses dynamic selection of classifiers to deal with concept drift. Basically, classifiers trained on new supervised batches available over time are add to a pool, from which is elected a custom ensemble for each test instance during the classification time.
Alceu de Souza Britto Júnior, Robert Sabourin   +1 more
exaly   +3 more sources

Handling Different Levels of Granularity within Naive Bayes Classifiers

Lecture Notes in Computer Science, 2013
Data mining techniques usually require a flat data table as input. For categorical attributes, there is often no canonical flat data table, since they can often be considered in different levels of granularity like continent, country or local region. The choice of the best level of granularity for a data mining task can be very tedious, especially when
Frank Klawonn
exaly   +3 more sources