AIMC Topic: Humans

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Detecting Large Vessel Occlusion at Multiphase CT Angiography by Using a Deep Convolutional Neural Network.

Radiology
Background Large vessel occlusion (LVO) stroke is one of the most time-sensitive diagnoses in medicine and requires emergent endovascular therapy to reduce morbidity and mortality. Leveraging recent advances in deep learning may facilitate rapid dete...

An entropy-based approach to detect and localize intraoperative bleeding during minimally invasive surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: During minimally invasive surgery (either robotic or traditional laparoscopic), vascular injuries may occur because of inadvertent surgical tool movements or actions. These vascular injuries can lead to arterial or venous bleeding with va...

Prognostic machine learning models for COVID-19 to facilitate decision making.

International journal of clinical practice
An increasing number of COVID-19 cases worldwide has overwhelmed the healthcare system. Physicians are struggling to allocate resources and to focus their attention on high-risk patients, partly because early identification of high-risk individuals i...

Transfer Learning Based Automatic Human Identification using Dental Traits- An Aid to Forensic Odontology.

Journal of forensic and legal medicine
Forensic Odontology deals with identifying humans based on their dental traits because of their robust nature. Classical methods of human identification require more manual effort and are difficult to use for large number of Images. A Novel way of au...

Machine learning prediction of the adverse outcome for nontraumatic subarachnoid hemorrhage patients.

Annals of clinical and translational neurology
OBJECTIVE: Subarachnoid hemorrhage (SAH) is often devastating with increased early mortality, particularly in those with presumed delayed cerebral ischemia (DCI). The ability to accurately predict survival for SAH patients during the hospital course ...

AI in the treatment of fertility: key considerations.

Journal of assisted reproduction and genetics
Artificial intelligence (AI) has been proposed as a potential tool to help address many of the existing problems related with empirical or subjective assessments of clinical and embryological decision points during the treatment of infertility. AI te...

Claims-Based Algorithms for Identifying Patients With Pulmonary Hypertension: A Comparison of Decision Rules and Machine-Learning Approaches.

Journal of the American Heart Association
Background Real-world healthcare data are an important resource for epidemiologic research. However, accurate identification of patient cohorts-a crucial first step underpinning the validity of research results-remains a challenge. We developed and e...

Artificial intelligence in cardiothoracic surgery.

Minerva cardioangiologica
The tremendous and rapid technological advances that humans have achieved in the last decade have definitely impacted how surgical tasks are performed in the operating room (OR). As a high-tech work environment, the contemporary OR has incorporated n...

Public Perceptions of Artificial Intelligence and Robotics in Medicine.

Journal of endourology
To understand better the public perception and comprehension of medical technology such as artificial intelligence (AI) and robotic surgery. In addition to this, to identify sensitivity to their use to ensure acceptability and quality of counseling....

Improvement of P300-Based Brain-Computer Interfaces for Home Appliances Control by Data Balancing Techniques.

Sensors (Basel, Switzerland)
The oddball paradigm used in P300-based brain-computer interfaces (BCIs) intrinsically poses the issue of data imbalance between target stimuli and nontarget stimuli. Data imbalance can cause overfitting problems and, consequently, poor classificatio...