AIMC Topic: Humans

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Semantic segmentation to identify bladder layers from H&E Images.

Diagnostic pathology
BACKGROUND: Identification of bladder layers is a necessary prerequisite to bladder cancer diagnosis and prognosis. We present a method of multi-class image segmentation, which recognizes urothelium, lamina propria, muscularis propria, and muscularis...

Deep user identification model with multiple biometric data.

BMC bioinformatics
BACKGROUND: Recognition is an essential function of human beings. Humans easily recognize a person using various inputs such as voice, face, or gesture. In this study, we mainly focus on DL model with multi-modality which has many benefits including ...

Leveraging Multimodal Deep Learning Architecture with Retina Lesion Information to Detect Diabetic Retinopathy.

Translational vision science & technology
PURPOSE: To improve disease severity classification from fundus images using a hybrid architecture with symptom awareness for diabetic retinopathy (DR).

Expressing uncertainty in Human-Robot interaction.

PloS one
Most people struggle to understand probability which is an issue for Human-Robot Interaction (HRI) researchers who need to communicate risks and uncertainties to the participants in their studies, the media and policy makers. Previous work showed tha...

Primary Robot-assisted Retroperitoneal Lymph Node Dissection for Men with Nonseminomatous Germ Cell Tumor: Experience from a Multi-institutional Cohort.

European urology focus
BACKGROUND: Primary robot-assisted retroperitoneal lymph node dissection (RA-RPLND) for men with nonseminomatous germ cell tumor (NSGCT) is an alternative to open RPLND for stage I and select stage II patients.

Deep learning for small and big data in psychiatry.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Psychiatry today must gain a better understanding of the common and distinct pathophysiological mechanisms underlying psychiatric disorders in order to deliver more effective, person-tailored treatments. To this end, it appears that the analysis of '...

Performance of deep learning object detection technology in the detection and diagnosis of maxillary sinus lesions on panoramic radiographs.

Dento maxillo facial radiology
OBJECTIVE: The first aim of this study was to determine the performance of a deep learning object detection technique in the detection of maxillary sinuses on panoramic radiographs. The second aim was to clarify the performance in the classification ...

A deep learning approach for magnetization transfer contrast MR fingerprinting and chemical exchange saturation transfer imaging.

NeuroImage
Semisolid magnetization transfer contrast (MTC) and chemical exchange saturation transfer (CEST) MRI based on MT phenomenon have shown potential to evaluate brain development, neurological, psychiatric, and neurodegenerative diseases. However, a qual...

Identifying scenarios of benefit or harm from kidney transplantation during the COVID-19 pandemic: A stochastic simulation and machine learning study.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candidates and recipients may face increased acquisition risks and case fatality rates (CFRs). Given our po...

Empathetic application of machine learning may address appropriate utilization of ART.

Reproductive biomedicine online
The value of artificial intelligence to benefit infertile patients is a subject of debate. This paper presents the experience of one aspect of artificial intelligence, machine learning, coupled with patient empathy to improve utilization of assisted ...