AIMC Topic: Humans

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PVRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Human motion prediction, which aims to predict future human poses given past poses, has recently seen increased interest. Many recent approaches are based on Recurrent Neural Networks (RNN) which model human poses with exponential maps. These approac...

Effects of galectin-1 on immunomodulatory properties of human monocyte-derived dendritic cells.

Growth factors (Chur, Switzerland)
Our study aimed to evaluate the effects of Gal-1 in dose depending manner on maturation and immunomodulatory properties of monocyte-derived (Mo) DCs . The effects were analyzed by monitoring their phenotypic characteristics, cytokine profile, and the...

Is off-clamp robot-assisted partial nephrectomy beneficial for renal function? Data from the CLOCK trial.

BJU international
OBJECTIVES: To compare the functional outcomes of on- vs off-clamp robot-assisted partial nephrectomy (RAPN) within a randomized controlled trial (RCT).

A Hybrid Brain-Computer Interface for Real-Life Meal-Assist Robot Control.

Sensors (Basel, Switzerland)
Assistant devices such as meal-assist robots aid individuals with disabilities and support the elderly in performing daily activities. However, existing meal-assist robots are inconvenient to operate due to non-intuitive user interfaces, requiring ad...

Machine learning approach to discovery of small molecules with potential inhibitory action against vasoactive metalloproteases.

Molecular diversity
With the advancement of combinatorial chemistry and big data, drug repositioning has boomed. In this sense, machine learning and artificial intelligence techniques offer a priori information to identify the most promising candidates. In this study, w...

3D Deep Learning Model for the Pretreatment Evaluation of Treatment Response in Esophageal Carcinoma: A Prospective Study (ChiCTR2000039279).

International journal of radiation oncology, biology, physics
PURPOSE: To develop and validate a pretreatment computed tomography (CT)-based deep-learning (DL) model for predicting the treatment response to concurrent chemoradiation therapy (CCRT) among patients with locally advanced thoracic esophageal squamou...

A fusion decision system to identify and grade malnutrition in cancer patients: Machine learning reveals feasible workflow from representative real-world data.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND AND AIMS: Most nutritional assessment tools are based on pre-defined questionnaires or consensus guidelines. However, it has been postulated that population data can be used directly to develop a solution for assessing malnutrition. This s...

Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trial.

Journal of gastroenterology
BACKGROUND: We have developed the computer-aided detection (CADe) system using an original deep learning algorithm based on a convolutional neural network for assisting endoscopists in detecting colorectal lesions during colonoscopy. The aim of this ...