AIMC Topic: Reproducibility of Results

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Enhancing Human-Robot Collaboration through a Multi-Module Interaction Framework with Sensor Fusion: Object Recognition, Verbal Communication, User of Interest Detection, Gesture and Gaze Recognition.

Sensors (Basel, Switzerland)
With the increasing presence of robots in our daily lives, it is crucial to design interaction interfaces that are natural, easy to use and meaningful for robotic tasks. This is important not only to enhance the user experience but also to increase t...

Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learning.

European radiology
OBJECTIVES: To use convolutional neural network for fully automated segmentation and radiomics features extraction of hypopharyngeal cancer (HPC) tumor in MRI.

Characterizing Uncertainty in Machine Learning for Chemistry.

Journal of chemical information and modeling
Characterizing uncertainty in machine learning models has recently gained interest in the context of machine learning reliability, robustness, safety, and active learning. Here, we separate the total uncertainty into contributions from noise in the d...

Trustworthy artificial intelligence and ethical design: public perceptions of trustworthiness of an AI-based decision-support tool in the context of intrapartum care.

BMC medical ethics
BACKGROUND: Despite the recognition that developing artificial intelligence (AI) that is trustworthy is necessary for public acceptability and the successful implementation of AI in healthcare contexts, perspectives from key stakeholders are often ab...

Functional Alignment-Auxiliary Generative Adversarial Network-Based Visual Stimuli Reconstruction via Multi-Subject fMRI.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Functional Magnetic Resonance Imaging (fMRI) provides more precise spatial and temporal information to reconstruct stimulus images than other technologies that can be used to measure the human brain's neural responses. The fMRI scans, however, genera...

Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES.

Journal of computer-aided molecular design
Using generative deep learning models and reinforcement learning together can effectively generate new molecules with desired properties. By employing a multi-objective scoring function, thousands of high-scoring molecules can be generated, making th...

Accuracy and clinical validity of automated cephalometric analysis using convolutional neural networks.

Orthodontics & craniofacial research
BACKGROUND: This study aimed to assess the error range of cephalometric measurements based on the landmarks detected using cascaded CNNs and determine how horizontal and vertical positional errors of individual landmarks affect lateral cephalometric ...

Evaluating the Accuracy and Reliability of Blowout Fracture Area Measurement Methods: A Review and the Potential Role of Artificial Intelligence.

The Journal of craniofacial surgery
Blowout fractures are a common type of facial injury that requires accurate measurement of the fracture area for proper treatment planning. This systematic review aimed to summarize and evaluate the current methods for measuring blowout fracture area...

Performance of retinal fluid monitoring in OCT imaging by automated deep learning versus human expert grading in neovascular AMD.

Eye (London, England)
PURPOSE: To evaluate the reliability of automated fluid detection in identifying retinal fluid activity in OCT scans of patients treated with anti-VEGF therapy for neovascular age-related macular degeneration by correlating human expert and automated...

Leveraging mid-infrared spectroscopic imaging and deep learning for tissue subtype classification in ovarian cancer.

The Analyst
Mid-infrared spectroscopic imaging (MIRSI) is an emerging class of label-free techniques being leveraged for digital histopathology. Modern histopathologic identification of ovarian cancer involves tissue staining followed by morphological pattern re...