AIMC Topic: Humans

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Robust classification of cell cycle phase and biological feature extraction by image-based deep learning.

Molecular biology of the cell
Across the cell cycle, the subcellular organization undergoes major spatiotemporal changes that could in principle contain biological features that could potentially represent cell cycle phase. We applied convolutional neural network-based classifier...

Brain tumor segmentation and grading of lower-grade glioma using deep learning in MRI images.

Computers in biology and medicine
Gliomas are the most common malignant brain tumors with different grades that highly determine the rate of survival in patients. Tumor segmentation and grading using magnetic resonance imaging (MRI) are common and essential for diagnosis and treatmen...

Deep learning for mass detection in Full Field Digital Mammograms.

Computers in biology and medicine
In recent years, the use of Convolutional Neural Networks (CNNs) in medical imaging has shown improved performance in terms of mass detection and classification compared to current state-of-the-art methods. This paper proposes a fully automated frame...

Should We Ignore, Follow, or Biopsy? Impact of Artificial Intelligence Decision Support on Breast Ultrasound Lesion Assessment.

AJR. American journal of roentgenology
The objective of this study was to assess the impact of artificial intelligence (AI)-based decision support (DS) on breast ultrasound (US) lesion assessment. A multicenter retrospective review of 900 breast lesions (470/900 [52.2%] benign; 430/900 ...

Learned optical flow for intra-operative tracking of the retinal fundus.

International journal of computer assisted radiology and surgery
PURPOSE: Sustained delivery of regenerative retinal therapies by robotic systems requires intra-operative tracking of the retinal fundus. We propose a supervised deep convolutional neural network to densely predict semantic segmentation and optical f...

Perioperative margin detection in basal cell carcinoma using a deep learning framework: a feasibility study.

International journal of computer assisted radiology and surgery
PURPOSE: Basal cell carcinoma (BCC) is the most commonly diagnosed cancer and the number of diagnosis is growing worldwide due to increased exposure to solar radiation and the aging population. Reduction of positive margin rates when removing BCC lea...

Leveraging vision and kinematics data to improve realism of biomechanic soft tissue simulation for robotic surgery.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical simulations play an increasingly important role in surgeon education and developing algorithms that enable robots to perform surgical subtasks. To model anatomy, finite element method (FEM) simulations have been held as the gold sta...

Electronic skins and machine learning for intelligent soft robots.

Science robotics
Soft robots have garnered interest for real-world applications because of their intrinsic safety embedded at the material level. These robots use deformable materials capable of shape and behavioral changes and allow conformable physical contact for ...

Deep learning in mental health outcome research: a scoping review.

Translational psychiatry
Mental illnesses, such as depression, are highly prevalent and have been shown to impact an individual's physical health. Recently, artificial intelligence (AI) methods have been introduced to assist mental health providers, including psychiatrists a...

Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.

Nutrients
Obesity is a global health problem with wide-reaching economic and social implications. Nutrition surveillance systems are essential to understanding and addressing poor dietary practices. However, diets are incredibly diverse across populations and ...