AIMC Topic: Humans

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A deep learning model for assistive decision-making during robot-aided rehabilitation therapies based on therapists' demonstrations.

Journal of neuroengineering and rehabilitation
BACKGROUND: A promising approach to improving motor recovery during rehabilitation is the use of robotic rehabilitation devices. These robotic devices provide tools to monitor the patient's recovery progress while providing highly standardized and in...

Empowering medical students with AI writing co-pilots: design and validation of AI self-assessment toolkit.

BMC medical education
BACKGROUND AND OBJECTIVES: Assessing and improving academic writing skills is a crucial component of higher education. To support students in this endeavor, a comprehensive self-assessment toolkit was developed to provide personalized feedback and gu...

Design strategies for artificial intelligence based future learning centers in medical universities.

BMC medical education
BACKGROUND: This study explores the acceptance of artificial intelligence(AI) tools in medical students and its influencing factors, thus providing theoretical basis and practical guidance for the construction of future learning centers in medical un...

Optimizing hypoglycaemia prediction in type 1 diabetes with Ensemble Machine Learning modeling.

BMC medical informatics and decision making
BACKGROUND: Type 1 diabetes (T1D) is a chronic endocrine disorder characterized by high blood glucose levels, impacting millions of people globally. Its management requires intensive insulin therapy, frequent blood glucose monitoring, and lifestyle a...

Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches.

BMC medical informatics and decision making
BACKGROUND: The aim of this study was to evaluate the potential models to determine the most important anthropometric factors associated with type 2 diabetes mellitus (T2DM).

A comparative analysis of LSTM models aided with attention and squeeze and excitation blocks for activity recognition.

Scientific reports
Human Activity Recognition plays a vital role in various fields, such as healthcare and smart environments. Traditional HAR methods rely on sensor or video data, but sensor-based systems have gained popularity due to their non-intrusive nature. Curre...

Chaotic gradient based optimization with fuzzy temporal optimized CNN for heart failure prediction.

Scientific reports
Heart failure is a leading cause of premature death, especially among individuals with a sedentary lifestyle. Early and accurate detection is essential to prevent the progression of this situation. However, many existing prediction systems failed to ...

Automated strabismus detection and classification using deep learning analysis of facial images.

Scientific reports
Strabismus, or eye misalignment, is a common condition affecting individuals of all ages. Early detection and accurate classification are essential for proper treatment and avoiding long-term complications. This research presents a new deep-learning-...

Localization and detection of deepfake videos based on self-blending method.

Scientific reports
Deepfake technology, which encompasses various video manipulation techniques implemented through deep learning algorithms-such as face swapping and expression alteration-has advanced to generate fake videos that are increasingly difficult for human o...

A survey of obstetric ultrasound uses and priorities for artificial intelligence-assisted obstetric ultrasound in low- and middle-income countries.

Scientific reports
Obstetric ultrasound (OBUS) is recommended as part of antenatal care for pregnant individuals worldwide. To better understand current uses of OBUS in low- and middle-income countries and perceptions regarding potential use of artificial intelligence ...