AIMC Topic: Prospective Studies

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Contrast-enhanced harmonic endoscopic ultrasound (CH-EUS) MASTER: A novel deep learning-based system in pancreatic mass diagnosis.

Cancer medicine
BACKGROUND AND AIMS: Distinguishing pancreatic cancer from nonneoplastic masses is critical and remains a clinical challenge. The study aims to construct a deep learning-based artificial intelligence system to facilitate pancreatic mass diagnosis, an...

Predicting decompression surgery by applying multimodal deep learning to patients' structured and unstructured health data.

BMC medical informatics and decision making
BACKGROUND: Low back pain (LBP) is a common condition made up of a variety of anatomic and clinical subtypes. Lumbar disc herniation (LDH) and lumbar spinal stenosis (LSS) are two subtypes highly associated with LBP. Patients with LDH/LSS are often s...

Quo Vadis, Amadeo Hand Robot? A Randomized Study with a Hand Recovery Predictive Model in Subacute Stroke.

International journal of environmental research and public health
BACKGROUND: Early identification of hand-prognosis-factors at patient's admission could help to select optimal synergistic rehabilitation programs based on conventional (COHT) or robot-assisted (RAT) therapies.

Prognostic significance of pulmonary arterial wedge pressure estimated by deep learning in acute heart failure.

ESC heart failure
AIMS: Acute decompensated heart failure (ADHF) presents with pulmonary congestion, which is caused by an increased pulmonary arterial wedge pressure (PAWP). PAWP is strongly associated with prognosis, but its quantitative evaluation is often difficul...

[Robots in visceral and thoracic surgery-Quo vadis?].

Chirurgie (Heidelberg, Germany)
Robotic surgical systems are now an inherent part of the German hospital landscape. In recent years, there has been an enormous increase in installed systems and operations performed, especially in abdominal surgery. Even though there is a lack of st...

Low-contrast-dose liver CT using low monoenergetic images with deep learning-based denoising for assessing hepatocellular carcinoma: a randomized controlled noninferiority trial.

European radiology
OBJECTIVE: Low monoenergetic images obtained using noise-reduction techniques may reduce CT contrast media requirements. We aimed to investigate the effectiveness of low-contrast-dose CT using dual-energy CT and deep learning-based denoising (DLD) te...

An accurate deep learning model for wheezing in children using real world data.

Scientific reports
Auscultation is an important diagnostic method for lung diseases. However, it is a subjective modality and requires a high degree of expertise. To overcome this constraint, artificial intelligence models are being developed. However, these models req...

Emulating future neurotechnology using magic.

Consciousness and cognition
Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion...