Results 251 to 260 of about 46,859 (313)

A Firefly Optimization Algorithm for Hyperparameter Tuning of the Support Vector Classifier to Predict Water Potability

Anupkumar M. Bongale, A. C., Santoshkumar Biradar, Kavita Tukaram Patil, Yogeshwari V. Mahajan, Deepak Dharrao, Siddhaling Urolagin, P. Olof Olsson   +7 more
openalex   +2 more sources

Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults

Annals of Gastroenterological Surgery, EarlyView.
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males, Marko Kumric, Zvonimir Boban, Josip Vrdoljak, Dario Pecenkovic, Matej Ivanda, Marko Grahovac, Zenon Pogorelic, Josko Bozic   +8 more
wiley   +1 more source

A novel hybrid framework integrating GA-driven 3D ResUNetGAN for MRI brain tumor segmentation. [PDF]

PLoS One
Kirubakaran M, Mohan J.
europepmc   +1 more source

Hyperparameter Optimization of XGBoost on Air Pollution and Respiratory Health Data

Gabriel Fuscald Scursone, Diana F. Adamatti, Flávio Manoel Rodrigues da Silva Júnior, Ronan Adler Tavella, Alícia da Silva Bonifácio, Ricardo Arend Machado, Daniel Pereira Ferreira, Washington Luiz Félix Correia Filho   +7 more
openalex   +2 more sources

Artificial Intelligence–Based Surgical Phase Analysis Enables Objective Assessment of Surgeon Skill in Robotic Distal Gastrectomy: A Multicenter Study

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim Artificial intelligence (AI)–based surgical video analysis can automate time‐consuming manual assessments and enable objective characterization of surgical workflows. We aimed to construct a large, multicenter, fully annotated dataset of robotic distal gastrectomy (RDG) videos and evaluate the feasibility and performance of an AI model for
Masaru Komatsu, Daichi Kitaguchi, Yoichi Ninomiya, Yuya Takabe, Mitsumasa Yoshida, Masahiro Yura, Nobuyoshi Takeshita, Takahiro Kinoshita, Masaaki Ito   +8 more
wiley   +1 more source

Adaptive Riemannian optimization for multi-scale diffeomorphic matching. [PDF]

Nat Commun
Jena R, Chaudhari P, Gee JC.
europepmc   +1 more source

Hyperparameter Optimization with Evolutionary Computing for Mental Health State Prediction

, 2018
Marius Wilhelm Olstad
openalex   +1 more source

Hyperparameters and their ranges for optimization in the credit risk prediction method.

Cai Yuanqing (22513351), Zhenming Gao (11789955), Zhang Jian (9250393), Roohallah Alizadehsani (6445298), Paweł Pławiak (17328063)   +4 more
openalex   +1 more source

Dictionary‐based weak‐form training for noise‐robust series hybrid models with multiplicative unknowns

AIChE Journal, EarlyView.
ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho, Akshay Kudva, Parth Shah, Dongheon Lee, Joseph Sang‐Il Kwon   +4 more
wiley   +1 more source

Temporal forecasting of electric vehicle charging load using an IVY-VMD-TCN-BiLSTM model with cross-zone evaluation. [PDF]

Sci Rep
Zhang W, Ma B, Wang D.
europepmc   +1 more source