AIMC Topic: Humans

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Optimizing Skin Cancer Diagnosis: A Modified Ensemble Convolutional Neural Network for Classification.

Microscopy research and technique
Skin cancer is recognized as one of the most harmful cancers worldwide. Early detection of this cancer is an effective measure for treating the disease efficiently. Traditional skin cancer detection methods face scalability challenges and overfitting...

Untargeted metabolomics and machine learning unveil the exposome and metabolism linked with the risk of early pregnancy loss.

Journal of hazardous materials
Early pregnancy loss (EPL) may result from exposure to emerging contaminants (ECs), although the underlying mechanisms remain poorly understood. This case-control study measured over 2000 serum features, including 37 ECs, 6 biochemicals, and 2057 end...

COSTA: Contrastive Spatial and Temporal Debiasing framework for next POI recommendation.

Neural networks : the official journal of the International Neural Network Society
Current research on next point-of-interest (POI) recommendation focuses on capturing users' behavior patterns residing in their mobility trajectories. However, the learning process will inevitably cause discrepancies between the recommendation and in...

A prompt tuning method based on relation graphs for few-shot relation extraction.

Neural networks : the official journal of the International Neural Network Society
Prompt-tuning has recently proven effective in addressing few-shot tasks. However, task resources remain severely limited in the specific domain of few-shot relation extraction. Despite its successes, prompt-tuning faces challenges distinguishing bet...

NLP for Analyzing Electronic Health Records and Clinical Notes in Cancer Research: A Review.

Journal of pain and symptom management
This review examines the application of natural language processing (NLP) techniques in cancer research using electronic health records (EHRs) and clinical notes. It addresses gaps in existing literature by providing a broader perspective than previo...

The Value of Artificial Intelligence in Prostate-Specific Membrane Antigen Positron Emission Tomography: An Update.

Seminars in nuclear medicine
This review aims to provide an up-to-date overview of the utility of artificial intelligence (AI) in evaluating prostate-specific membrane antigen (PSMA) positron emission tomography (PET) scans for prostate cancer (PCa). A literature review was cond...

Using natural language processing to identify patterns associated with depression, anxiety, and stress symptoms during the COVID-19 pandemic.

Journal of affective disorders
BACKGROUND: Combining data-driven natural language processing techniques with traditional methods using predefined word lists may offer greater insights into the connections between language patterns and depression and anxiety symptoms, particularly ...

A novel artificial intelligence framework to quantify the impact of clinical compared with nonclinical influences on postoperative length of stay.

Surgery
BACKGROUND: The relative proportion of clinical compared with nonclinical influences on length of stay after colectomy has never been measured. We developed a novel machine-learning framework that quantifies the proportion of length of stay after col...

Integrating Generative AI in Dental Education: A Scoping Review of Current Practices and Recommendations.

European journal of dental education : official journal of the Association for Dental Education in Europe
BACKGROUND: Generative AI (GenAI) tools like ChatGPT are increasingly relevant in dental education, offering potential enhancements in personalised learning and clinical reasoning. However, specific guidance from dental institutions remains unexplore...

TransAnaNet: Transformer-based anatomy change prediction network for head and neck cancer radiotherapy.

Medical physics
BACKGROUND: Adaptive radiotherapy (ART) can compensate for the dosimetric impact of anatomic change during radiotherapy of head-neck cancer (HNC) patients. However, implementing ART universally poses challenges in clinical workflow and resource alloc...