AIMC Topic: Humans

Clear Filters Showing 15951 to 15960 of 95995 articles

Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations.

Cell
Psychiatric disorders are influenced by genetic and environmental factors. However, their study is hindered by limitations on precisely characterizing human behavior. New technologies such as wearable sensors show promise in surmounting these limitat...

Enhancing AI reliability: A foundation model with uncertainty estimation for optical coherence tomography-based retinal disease diagnosis.

Cell reports. Medicine
Inability to express the confidence level and detect unseen disease classes limits the clinical implementation of artificial intelligence in the real world. We develop a foundation model with uncertainty estimation (FMUE) to detect 16 retinal conditi...

Faster and better than a physician?: Assessing diagnostic proficiency of ChatGPT in misdiagnosed individuals with neuromyelitis optica spectrum disorder.

Journal of the neurological sciences
BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is a commonly misdiagnosed condition. Driven by cost-consciousness and technological fluency, distinct generations may gravitate towards healthcare alternatives, including artificial intellig...

Explainable machine learning on clinical features to predict and differentiate Alzheimer's progression by sex: Toward a clinician-tailored web interface.

Journal of the neurological sciences
Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasiv...

Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide Properties.

Journal of chemical information and modeling
Peptides are crucial in biological processes and therapeutic applications. Given their importance, advancing our ability to predict peptide properties is essential. In this study, we introduce Multi-Peptide, an innovative approach that combines trans...

Use and Comparison of Machine Learning Techniques to Discern the Protein Patterns of Autoantibodies Present in Women with and without Breast Pathology.

Journal of proteome research
Breast cancer (BC) has become a global health problem, ranking first in incidence and fifth in mortality in women around the world. Although there are some diagnostic methods for the disease, these are not sufficiently effective and are invasive. In ...

Spine X-ray image segmentation based on deep learning and marker controlled watershed.

Journal of X-ray science and technology
BACKGROUND: The development of automatic methods for vertebral segmentation provides the objective analysis of each vertebra in the spine image, which is important for the diagnosis of various spinal diseases. However, vertebrae have inter-class simi...

Patient and practitioner perceptions around use of artificial intelligence within the English NHS diabetic eye screening programme.

Diabetes research and clinical practice
AIMS: Automated retinal image analysis using Artificial Intelligence (AI) can detect diabetic retinopathy as accurately as human graders, but it is not yet licensed in the NHS Diabetic Eye Screening Programme (DESP) in England. This study aims to ass...

Development of two machine learning models to predict conversion from primary HER2-0 breast cancer to HER2-low metastases: a proof-of-concept study.

ESMO open
BACKGROUND: HER2-low expression has gained clinical relevance in breast cancer (BC) due to the availability of anti-HER2 antibody-drug conjugates for patients with HER2-low metastatic BC. The well-reported instability of HER2-low status during diseas...