AIMC Topic: Humans

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Can We Quickly Learn to "Translate" Bioactive Molecules with Transformer Models?

Journal of chemical information and modeling
Meaningful exploration of the chemical space of druglike molecules in drug design is a highly challenging task due to a combinatorial explosion of possible modifications of molecules. In this work, we address this problem with transformer models, a t...

Superhuman artificial intelligence can improve human decision-making by increasing novelty.

Proceedings of the National Academy of Sciences of the United States of America
How will superhuman artificial intelligence (AI) affect human decision-making? And what will be the mechanisms behind this effect? We address these questions in a domain where AI already exceeds human performance, analyzing more than 5.8 million move...

Effects of Upper Limb Robot-Assisted Rehabilitation Compared with Conventional Therapy in Patients with Stroke: Preliminary Results on a Daily Task Assessed Using Motion Analysis.

Sensors (Basel, Switzerland)
Robotic rehabilitation of the upper limb has demonstrated promising results in terms of the improvement of arm function in post-stroke patients. The current literature suggests that robot-assisted therapy (RAT) is comparable to traditional approaches...

Domain Adaptation Methods for Lab-to-Field Human Context Recognition.

Sensors (Basel, Switzerland)
Human context recognition (HCR) using sensor data is a crucial task in Context-Aware (CA) applications in domains such as healthcare and security. Supervised machine learning HCR models are trained using smartphone HCR datasets that are scripted or g...

Convergence of Artificial Intelligence and Neuroscience towards the Diagnosis of Neurological Disorders-A Scoping Review.

Sensors (Basel, Switzerland)
Artificial intelligence (AI) is a field of computer science that deals with the simulation of human intelligence using machines so that such machines gain problem-solving and decision-making capabilities similar to that of the human brain. Neuroscien...

In Silico Screening and Optimization of Cell-Penetrating Peptides Using Deep Learning Methods.

Biomolecules
Cell-penetrating peptides (CPPs) have great potential to deliver bioactive agents into cells. Although there have been many recent advances in CPP-related research, it is still important to develop more efficient CPPs. The development of CPPs by in s...

Clinical efficacy of robot-assisted subxiphoid versus lateral thoracic approach in the treatment of anterior mediastinal tumors.

World journal of surgical oncology
BACKGROUND: The purpose of this study was to compare the perioperative efficacy and safety of da Vinci robot-assisted thoracoscopic surgery (RATS) for treating anterior mediastinal tumors through the subxiphoid and lateral thoracic approaches under t...

The predictive model for COVID-19 pandemic plastic pollution by using deep learning method.

Scientific reports
Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increased significantly throughout the world. These hazardous wastes play an important role in environmental...

Differentiating malignant and benign eyelid lesions using deep learning.

Scientific reports
Artificial intelligence as a screening tool for eyelid lesions will be helpful for early diagnosis of eyelid malignancies and proper decision-making. This study aimed to evaluate the performance of a deep learning model in differentiating eyelid lesi...

Persuading Patients Using Rhetoric to Improve Artificial Intelligence Adoption: Experimental Study.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) can transform health care processes with its increasing ability to translate complex structured and unstructured data into actionable clinical decisions. Although it has been established that AI is much more e...