Intelligent systems in healthcare: A systematic survey of explainable user interfaces.

With radiology shortages affecting over half of the global population, the potential of artificial intelligence to revolutionize medical diagnosis and treatment is ever more important. However, lacking trust from medical professionals hinders the widespread adoption of AI models in health sciences. Explainable AI (XAI) aims to increase trust and understanding of black box models by identifying biases and providing transparent explanations.

Shedding light on ai in radiology: A systematic review and taxonomy of eye gaze-driven interpretability in deep learning.

X-ray imaging plays a crucial role in diagnostic medicine. Yet, a significant portion of the global population lacks access to this essential technology due to a shortage of trained radiologists. Eye-tracking data and deep learning models can enhance X-ray analysis by mapping expert focus areas, guiding automated anomaly detection, optimizing workflow efficiency, and bolstering training methods for novice radiologists.

MDF-Net for abnormality detection by fusing X-rays with clinical data.

This study investigates the effects of including patients' clinical information on the performance of deep learning (DL) classifiers for disease location in chest X-ray images. Although current classifiers achieve high performance using chest X-ray images alone, consultations with practicing radiologists indicate that clinical data is highly informative and essential for interpreting medical images and making proper diagnoses. In this work, we propose a novel architecture consisting of two fusion methods that enable the model to simultaneously process patients' clinical data (structured data) and chest X-rays (image data).

A Survey on Remote Assistance and Training in Mixed Reality Environments.

The recent pandemic, war, and oil crises have caused many to reconsider their need to travel for education, training, and meetings. Providing assistance and training remotely has thus gained importance for many applications, from industrial maintenance to surgical telemonitoring. Current solutions such as video conferencing platforms lack essential communication cues such as spatial referencing, which negatively impacts both time completion and task performance.

Touchless interaction with medical images based on 3D hand cursors supported by single-foot input: A case study in dentistry.

Feet input can support mid-air hand gestures for touchless medical image manipulation to prevent unintended activations, especially in sterile contexts. However, foot interaction has yet to be investigated in dental settings. In this paper, we conducted a mixed methods research study with medical dentistry professionals.

CavBench: A benchmark for protein cavity detection methods.

Extensive research has been applied to discover new techniques and methods to model protein-ligand interactions. In particular, considerable efforts focused on identifying candidate binding sites, which quite often are active sites that correspond to protein pockets or cavities. Thus, these cavities play an important role in molecular docking.

Magic Carpet: Interaction Fidelity for Flying in VR.

Locomotion in virtual environments is currently a difficult and unnatural task to perform. Normally, researchers tend to devise ground- or floor-based metaphors to constrain the degrees of freedom (DoFs) during motion. These restrictions enable interactions that accurately emulate the human gait to provide high interaction fidelity.

On a "Columbus' Egg": Modeling the shape of asymptomatic, dysplastic and impinged hip joints.

Understanding morphological features that characterize normal hip joint is critical and necessary for a more comprehensive definition of pathological presentations, such as femoroacetabular impingement and hip dysplasia. Based on anatomical observations that articular surfaces of synovial joints are better represented by ovoidal shapes than by spheres, the aim of this study is to computationally test this morphological classification for the femoral head and acetabular cavity of asymptomatic, dysplastic and impinged hips by comparing spherical, ellipsoidal and ovoidal shapes. An image-based surface fitting framework was used to assess the goodness-of-fit of spherical, ellipsoidal and tapered ellipsoidal (i.

Geometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Survey.

Detecting and analyzing protein cavities provides significant information about active sites for biological processes (e.g., protein-protein or protein-ligand binding) in molecular graphics and modeling.

On the utility of 3D hand cursors to explore medical volume datasets with a touchless interface.

Analyzing medical volume datasets requires interactive visualization so that users can extract anatomo-physiological information in real-time. Conventional volume rendering systems rely on 2D input devices, such as mice and keyboards, which are known to hamper 3D analysis as users often struggle to obtain the desired orientation that is only achieved after several attempts. In this paper, we address which 3D analysis tools are better performed with 3D hand cursors operating on a touchless interface comparatively to a 2D input devices running on a conventional WIMP interface.