AIMC Topic: Humans

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Clinically applicable semi-supervised learning framework for multiple organs at risk and tumor delineation in lung cancer brachytherapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lung cancer in practical clinical applications remains under-validated. We reported an investigation that validated a robust semi-supervised conditional ...

MIO: An ontology for annotating and integrating medical knowledge in myocardial infarction to enhance clinical decision making.

Computers in biology and medicine
As biotechnology and computer science continue to advance, there's a growing amount of biomedical data worldwide. However, standardizing and consolidating these data remains challenging, making analysis and comprehension more difficult. To enhance re...

Integrating lightweight convolutional neural network with entropy-informed channel attention and adaptive spatial attention for OCT-based retinal disease classification.

Computers in biology and medicine
This article proposes an effective and lightweight contextual convolutional neural network architecture called LOCT-Net for classifying retinal diseases. The LOCT-Net adopts nested residual blocks to capture the local patterns from the optical cohere...

Enhancing cell instance segmentation in scanning electron microscopy images via a deep contour closing operator.

Computers in biology and medicine
Accurately segmenting and individualizing cells in scanning electron microscopy (SEM) images is a highly promising technique for elucidating tissue architecture in oncology. While current artificial intelligence (AI)-based methods are effective, erro...

Multimodal learning-based speech enhancement and separation, recent innovations, new horizons, challenges and real-world applications.

Computers in biology and medicine
With the increasing global prevalence of disabling hearing loss, speech enhancement technologies have become crucial for overcoming communication barriers and improving the quality of life for those affected. Multimodal learning has emerged as a powe...

DALL-M: Context-aware clinical data augmentation with large language models.

Computers in biology and medicine
X-ray images are vital in medical diagnostics, but their effectiveness is limited without clinical context. Radiologists often find chest X-rays insufficient for diagnosing underlying diseases, necessitating the integration of structured clinical fea...

A novel skeletal muscle quantitative method and deep learning-based sarcopenia diagnosis for cervical cancer patients treated with radiotherapy.

Medical physics
BACKGROUND: Sarcopenia is associated with decreased survival in cervical cancer patients treated with radiotherapy. Cone-beam computed tomography (CBCT) was widely used in image-guided radiotherapy. Sarcopenia is assessed by the skeletal muscle index...

Generation of surgical reports for lymph node dissection during laparoscopic gastric cancer surgery based on artificial intelligence.

International journal of computer assisted radiology and surgery
PURPOSE: This study aimed to develop an artificial intelligence (AI) model for the surgical report output of laparoscopic lymph node dissection in the suprapancreatic region during gastric cancer surgery.

Transforming Healthcare: Intelligent Wearable Sensors Empowered by Smart Materials and Artificial Intelligence.

Advanced materials (Deerfield Beach, Fla.)
Intelligent wearable sensors, empowered by machine learning and innovative smart materials, enable rapid, accurate disease diagnosis, personalized therapy, and continuous health monitoring without disrupting daily life. This integration facilitates a...

Digital Technologies and Artificial Intelligence in Cardiac Rehabilitation: A Narrative Review.

Journal of cardiopulmonary rehabilitation and prevention
PURPOSE: This review explores the role and impact of digital technology in cardiac rehabilitation (CR), assessing its potential to enhance patient outcomes and address barriers to CR delivery.