AIMC Topic: Humans

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Exploring refined dual visual features cross-combination for image captioning.

Neural networks : the official journal of the International Neural Network Society
For current image caption tasks used to encode region features and grid features Transformer-based encoders have become commonplace, because of their multi-head self-attention mechanism, the encoder can better capture the relationship between differe...

Advancements in supervised deep learning for metal artifact reduction in computed tomography: A systematic review.

European journal of radiology
BACKGROUND: Metallic artefacts caused by metal implants, are a common problem in computed tomography (CT) imaging, degrading image quality and diagnostic accuracy. With advancements in artificial intelligence, novel deep learning (DL)-based metal art...

Bidirectional consistency with temporal-aware for semi-supervised time series classification.

Neural networks : the official journal of the International Neural Network Society
Semi-supervised learning (SSL) has achieved significant success due to its capacity to alleviate annotation dependencies. Most existing SSL methods utilize pseudo-labeling to propagate useful supervised information for training unlabeled data. Howeve...

Rule-based natural language processing to examine variation in worsening heart failure hospitalizations by age, sex, race and ethnicity, and left ventricular ejection fraction.

American heart journal
BACKGROUND: Prior studies characterizing worsening heart failure events (WHFE) have been limited in using structured healthcare data from hospitalizations, and with little exploration of sociodemographic variation. The current study examined the impa...

Development of a novel prognostic signature derived from super-enhancer-associated gene by machine learning in head and neck squamous cell carcinoma.

Oral oncology
Dysregulated super-enhancer (SE) results in aberrant transcription that drives cancer initiation and progression. SEs have been demonstrated as novel promising diagnostic/prognostic biomarkers and therapeutic targets across multiple human cancers. He...

Generative AI in Pediatric Gastroenterology.

Current gastroenterology reports
PURPOSE OF REVIEW: The integration of digital technology into medical practice is often thrust upon clinicians, with standards and routines developed long after initiation. Clinicians should endeavor towards a basic understanding even of emerging tec...

"Identifying complication risk factors in reduction mammaplasty: a single-center analysis of 1021 patients applying machine learning methods".

Updates in surgery
Various surgical approaches and pedicles have been described to ensure safe and satisfactory results in reduction mammaplasty. Although different breasts require different techniques, complications are common. This study aims to assess the incidence ...

Machine learning to attribute the source of Campylobacter infections in the United States: A retrospective analysis of national surveillance data.

The Journal of infection
OBJECTIVES: Integrating pathogen genomic surveillance with bioinformatics can enhance public health responses by identifying risk and guiding interventions. This study focusses on the two predominant Campylobacter species, which are commonly found in...

The EU Artificial Intelligence Act (2024): Implications for healthcare.

Health policy (Amsterdam, Netherlands)
In August 2024, the EU Artificial Intelligence Act (AI Act) entered into force. This legally binding instrument sets rules for the development, the placing on the market, the putting into service, and the use of AI systems in the European Union. As t...

Clinical impact of AI in radiology department management: a systematic review.

La Radiologia medica
PURPOSE: Artificial intelligence (AI) has revolutionized medical diagnosis and treatment. Breakthroughs in diagnostic applications make headlines, but AI in department administration (admin AI) likely deserves more attention. With the present study w...