Zobrazeno 1 - 10
of 1 442
pro vyhledávání: '"Automated machine learning"'
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 25, Iss , Pp 9-19 (2024)
Computational modeling has earned significant interest as an alternative to animal testing of toxicity assessment. However, the process of selecting an appropriate algorithm and fine-tuning hyperparameters for the developing of optimized models takes
Externí odkaz:
https://doaj.org/article/e7baf93ff550439596cf699e489d3676
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Time series classification finds widespread applications in civil, industrial, and military fields, while the classification performance of time series models has been improving with the recent development of deep learning. However, the issu
Externí odkaz:
https://doaj.org/article/a6c52420a31f4c208905d0a6e98b871e
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 36, Iss 1, Pp 88-93 (2024)
Class imbalance of the target variable is a common feature of quite a few areas. Classic machine learning models are not the best solution in this case, since there will be a prediction bias towards the majority class. To solve this problem, various
Externí odkaz:
https://doaj.org/article/d1efaeaf56df4096b88b6248f382aeb9
Publikováno v:
Chinese Medicine, Vol 19, Iss 1, Pp 1-14 (2024)
Abstract The aim of this study was to develop a machine learning-assisted rapid determination methodology for traditional Chinese Medicine Constitution. Based on the Constitution in Chinese Medicine Questionnaire (CCMQ), the most applied diagnostic i
Externí odkaz:
https://doaj.org/article/753116bc38ea4d239239af31ecfdf8d4
Autor:
Juho An, Il Seok Kim, Kwang-Ju Kim, Ji Hyun Park, Hyuncheol Kang, Hyuk Jung Kim, Young Sik Kim, Jung Hwan Ahn
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract This study evaluates the diagnostic efficacy of automated machine learning (AutoGluon) with automated feature engineering and selection (autofeat), focusing on clinical manifestations, and a model integrating both clinical manifestations and
Externí odkaz:
https://doaj.org/article/29c4f5c53432435ebf181f05261eafc5
Publikováno v:
Medicine Advances, Vol 2, Iss 3, Pp 205-237 (2024)
Abstract Machine learning (ML) has achieved substantial success in performing healthcare tasks in which the configuration of every part of the ML pipeline relies heavily on technical knowledge. To help professionals with borderline expertise to bette
Externí odkaz:
https://doaj.org/article/24e6e665f4c9483f9be2f2e0b7528049
Autor:
Teerachate Nantakeeratipat, Natchapon Apisaksirikul, Boonyaon Boonrojsaree, Sirapob Boonkijkullatat, Arida Simaphichet
Publikováno v:
Frontiers in Dental Medicine, Vol 5 (2024)
IntroductionTo detect dental plaque, manual assessment and plaque-disclosing dyes are commonly used. However, they are time-consuming and prone to human error. This study aims to investigate the feasibility of using Google Cloud's Vertex artificial i
Externí odkaz:
https://doaj.org/article/a6175248b895491a92bad2110d8e1f14
Autor:
Joonseo Ha, Heejun Roh
Publikováno v:
ICT Express, Vol 10, Iss 3, Pp 594-599 (2024)
Recently, QUIC for the secure and faster connections has standardized but it is unclear that QUIC can cope with website fingerprinting (WF), a technique to infer visited websites from network traffic, since most existing efforts targeted TCP-induced
Externí odkaz:
https://doaj.org/article/5962e2e44f2f4a93abf2f327d931dfe7
Publikováno v:
Genome Biology, Vol 25, Iss 1, Pp 1-18 (2024)
Abstract Background The advent of single-cell RNA-sequencing (scRNA-seq) has driven significant computational methods development for all steps in the scRNA-seq data analysis pipeline, including filtering, normalization, and clustering. The large num
Externí odkaz:
https://doaj.org/article/bd2e5f3db27e41d7ad62954a77822e45
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Gastrointestinal stromal tumors (GISTs) are a rare type of tumor that can develop liver metastasis (LIM), significantly impacting the patient's prognosis. This study aimed to predict LIM in GIST patients by constructing machine learning (ML)
Externí odkaz:
https://doaj.org/article/0eebdebb05f242739ffdf2189fbd9cd7