AIMC Topic: Humans

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Multiomic based Bayesian network toxicity modeling for simultaneous prediction of multiple toxicity outcomes in NSCLC.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Radiation Pneumonitis (RP) and Radiation Esophagitis (RE) are two prominent dose limiting toxicities from NSCLC radiotherapy. This study aimed to develop a multi-objective Bayesian network (BN) model to predict multiple NSCLC outcomes simult...

PedSemiSeg: Pedagogy-inspired semi-supervised polyp segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Recent advancements in deep learning techniques have contributed to developing improved polyp segmentation methods, thereby aiding in the diagnosis of colorectal cancer and facilitating automated surgery like endoscopic submucosal dissection (ESD). H...

Cephalometric landmark detection using vision transformers with direct coordinate prediction.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Cephalometric Landmark Detection (CLD), i.e. annotating interest points in lateral X-ray images, is the crucial first step of every orthodontic therapy. While CLD has immense potential for automation using Deep Learning methods, carefully crafted con...

Improving YOLO-based breast mass detection with transfer learning pretraining on the OPTIMAM Mammography Image Database.

Computers in biology and medicine
BACKGROUND AND OBJECTIVES: Early detection of breast cancer through mammography significantly improves survival rates. However, high false positive and false negative rates remain a challenge. Deep learning-based computer-aided diagnosis systems can ...

The role of data partitioning on the performance of EEG-based deep learning models in supervised cross-subject analysis: A preliminary study.

Computers in biology and medicine
Deep learning is significantly advancing the analysis of electroencephalography (EEG) data by effectively discovering highly nonlinear patterns within the signals. Data partitioning and cross-validation are crucial for assessing model performance and...

A deep learning model combining convolutional neural networks and a selective kernel mechanism for SSVEP-Based BCIs.

Computers in biology and medicine
Existing deep learning methods for brain-computer interfaces (BCIs) based on steady-state visually evoked potential (SSVEP) face several challenges, such as overfitting when training data are insufficient, and the difficulty of effectively capturing ...

The artificial intelligence challenge in rare disease diagnosis: A case study on collagen VI muscular dystrophy.

Computers in biology and medicine
The use of artificial intelligence (AI) techniques is significantly changing the analysis of medical images, accelerating and standardizing the diagnosis process. To train an AI model, however, a large dataset is typically required, especially when u...

Towards a Possible Definition of Consciousness.

Bio Systems
There is no consensus about what cognition and its emergent form, consciousness, are. Yet this article proposes a new definition of consciousness. As many researchers, philosophers and other thinkers believe that life means cognising, this new defini...

Advancing patient monitoring, diagnostics, and treatment strategies for transplant precision medicine.

Lancet (London, England)
Transplant medicine faces substantial challenges, as patients require lifelong immunosuppression to prevent graft rejection. Immunosuppressive regimens to date, while reasonably effective at preventing acute rejection, cause numerous health complicat...

Self-Healing Triboelectric Sensors with Enhanced Durability for Gesture Recognition and Human-Machine Interaction.

Nano letters
The emergence of triboelectric nanogenerators (TENGs) has significantly developed the landscape of wearable electronics. However, the durability and self-healing capabilities of TENGs remain challenging. Herein, a self-healing triboelectric nanogener...