Latest AI and machine learning research in adhd/add for healthcare professionals.
Cancer engineering for tumor normalization offers a promising therapeutic strategy to reverse malignant cells and their supportive tumor microenvironment into a more benign state. Herein, an artificial intelligence (AI) approach was developed using mRNA data from patients with lung adenocarcinoma to facilitate the identification of aberrant signaling pathways, specifically focusing on PD-L1, Wnt, ...
Light-field microscopy (LFM) and its variants have significantly advanced intravital high-speed 3D imaging. However, their practical applications remain limited due to trade-offs among processing speed, fidelity, and generalization in existing reconstruction methods. Here we propose a physics-driven self-supervised reconstruction network (SeReNet) for unscanned LFM and scanning LFM (sLFM) to achie...
Class distribution mismatch (CDM) refers to the discrepancy between class distributions in training data and target tasks. Previous methods address ...
We address the task of generating 3D hair geometry from a single image, which is challenging due to the diversity of hairstyles and the lack of pair...
Cervical cancer is a malignant tumor that endangers women's life and health. While deep learning has enhanced the accuracy of cervical cell classifica...
BACKGROUND: Attention-Deficit-Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental disorder that impacts cognitive control processes. Wh...
Colorectal cancer is one of the deadliest cancers today, but it can be prevented through early detection of malignant polyps in the colon, primarily...
Image steganography is a technique that conceals secret information in a cover image to achieve covert communication. Recent research has demonstrat...
The task of scene text editing is to modify or add texts on images while maintaining the fidelity of newly generated text and visual coherence with ...
Automatic segmentation of anatomical landmarks in endoscopic images can provide assistance to doctors and surgeons for diagnosis, treatments or medi...
Triage is used in emergency departments to ensure timely patient care according to urgency of treatment. However, triage accuracy and efficiency remai...
BACKGROUND: Good medical records are an essential part of healthcare. However, the burden of clinical documentation can reduce clinician productivity ...
This study systematically tests a computational power reuse scheme proposed by the open source community disabling specific instruction sets (Fused ...
Labeling errors in remote sensing (RS) image segmentation datasets often remain implicit and subtle due to ambiguous class boundaries, mixed pixels,...
Convolutional neural network (CNN) slides a kernel over the whole image to produce an output map. This kernel scheme reduces the number of parameter...
As centralized social media platforms face growing concerns, more users are seeking greater control over their social feeds and turning to decentral...
As extended reality (XR) is redefining how users interact with computing devices, research in human action recognition is gaining prominence. Typica...
Perceptual hashing is used to detect whether an input image is similar to a reference image with a variety of security applications. Recently, they ...
Text-to-image models based on diffusion processes, such as DALL-E, Stable Diffusion, and Midjourney, are capable of transforming texts into detailed...
The rapid advancement of diffusion models and personalization techniques has made it possible to recreate individual portraits from just a few publi...