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Benchmarking

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Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations.

Sensors (Basel, Switzerland)
This paper presents a new synthetic dataset obtained from Gazebo simulations of an Unmanned Ground Vehicle (UGV) moving on different natural environments. To this end, a Husky mobile robot equipped with a tridimensional (3D) Light Detection and Rangi...

Accurate somatic variant detection using weakly supervised deep learning.

Nature communications
Identification of somatic mutations in tumor samples is commonly based on statistical methods in combination with heuristic filters. Here we develop VarNet, an end-to-end deep learning approach for identification of somatic variants from aligned tumo...

MetaAge: Meta-Learning Personalized Age Estimators.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Different people age in different ways. Learning a personalized age estimator for each person is a promising direction for age estimation given that it better models the personalization of aging processes. However, most existing personalized methods ...

Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space.

Nature communications
Therapeutic antibody development requires selection and engineering of molecules with high affinity and other drug-like biophysical properties. Co-optimization of multiple antibody properties remains a difficult and time-consuming process that impede...

CNN-Based Brain Tumor Detection Model Using Local Binary Pattern and Multilayered SVM Classifier.

Computational intelligence and neuroscience
In this paper, an autonomous brain tumor segmentation and detection model is developed utilizing a convolutional neural network technique that included a local binary pattern and a multilayered support vector machine. The detection and classification...

Boosted Sine Cosine Algorithm with Application to Medical Diagnosis.

Computational and mathematical methods in medicine
The sine cosine algorithm (SCA) was proposed for solving optimization tasks, of which the way to obtain the optimal solution is mainly through the continuous iteration of the sine and cosine update formulas. However, SCA also faces low population div...

Towards a guideline for evaluation metrics in medical image segmentation.

BMC research notes
In the last decade, research on artificial intelligence has seen rapid growth with deep learning models, especially in the field of medical image segmentation. Various studies demonstrated that these models have powerful prediction capabilities and a...

Proficiency-based progression training for robotic surgery skills training: a randomized clinical trial.

BJU international
OBJECTIVE: To determine whether proficiency-based progression (PBP) training leads to better robotic surgical performance compared to traditional training (TT), given that the value of PBP training for learning robotic surgical skills is unclear.

Benchmarking Deep Learning Models for Tooth Structure Segmentation.

Journal of dental research
A wide range of deep learning (DL) architectures with varying depths are available, with developers usually choosing one or a few of them for their specific task in a nonsystematic way. Benchmarking (i.e., the systematic comparison of state-of-the ar...

Decisions are not all equal-Introducing a utility metric based on case-wise raters' perceptions.

Computer methods and programs in biomedicine
Background and Objective Evaluation of AI-based decision support systems (AI-DSS) is of critical importance in practical applications, nonetheless common evaluation metrics fail to properly consider relevant and contextual information. In this articl...