AIMC Topic: Humans

Clear Filters Showing 9111 to 9120 of 95995 articles

ALL diagnosis: can efficiency and transparency coexist? An explainble deep learning approach.

Scientific reports
Acute Lymphoblastic Leukemia (ALL) is a life-threatening malignancy characterized by its aggressive progression and detrimental effects on the hematopoietic system. Early and accurate diagnosis is paramount to optimizing therapeutic interventions and...

EFCNet enhances the efficiency of segmenting clinically significant small medical objects.

Scientific reports
Efficient segmentation of small hyperreflective dots, key biomarkers for diseases like macular edema, is critical for diagnosis and treatment monitoring.However, existing models, including Convolutional Neural Networks (CNNs) and Transformers, strugg...

Summarizing Online Patient Conversations Using Generative Language Models: Experimental and Comparative Study.

JMIR medical informatics
BACKGROUND: Social media is acknowledged by regulatory bodies (eg, the Food and Drug Administration) as an important source of patient experience data to learn about patients' unmet needs, priorities, and preferences. However, current methods rely ei...

Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: Crisis hotlines serve as a crucial avenue for the early identification of suicide risk, which is of paramount importance for suicide prevention and intervention. However, assessing the risk of callers in the crisis hotline context is cons...

Health Care Social Robots in the Age of Generative AI: Protocol for a Scoping Review.

JMIR research protocols
BACKGROUND: Social robots (SR), sensorimotor machines designed to interact with humans, can help to respond to the increasing demands in the health care sector. To ensure the successful use of this technology, acceptance is paramount. Generative arti...

Localisation and classification of multi-stage caries on CBCT images with a 3D convolutional neural network.

Clinical oral investigations
OBJECTIVES: Dental caries remains a significant global health concern. Recognising the diagnostic potential of cone-beam computed tomography (CBCT) in caries assessment, this study aimed to develop an artificial intelligence (AI)-driven tool for accu...

Comparison of artificial intelligence applications and commercial system performances using selected ANA IIF images.

Immunologic research
Accurate and accessible classification of anti-nuclear antibodies (ANA) through indirect immunofluorescence (IIF) imaging is crucial for diagnosing autoimmune diseases. However, many laboratories, particularly those with limited resources, lack acces...

Identification of Recurrence-associated Gene Signatures and Machine Learning-based Prediction in IDH-Wildtype Histological Glioblastoma.

Journal of molecular neuroscience : MN
Glioblastoma (GBM) is a highly aggressive brain tumor with frequent recurrence, yet the molecular mechanisms driving recurrence remain poorly understood. Identifying recurrence-associated genes may improve prognosis and treatment strategies. We appli...

Towards improved prescription metrics in novel radiotherapy techniques: a machine learning study.

Physics in medicine and biology
FLASH radiotherapy (RT), microbeam RT (MRT) and minibeam RT (MBRT) are novel RT techniques that have been shown to reduce normal tissue complication probabilities, by modulating the dose distributions through different parameters in space and time. T...

A dual-branch hybrid network with bilateral-difference awareness for collateral scoring on CT angiography of acute ischemic stroke patients.

Physics in medicine and biology
Acute ischemic stroke (AIS) patients with good collaterals tend to have better outcomes after endovascular therapy. Existing collateral scoring methods rely mainly on vessel segmentation and convolutional neural networks (CNNs), often ignoring bilate...