AIMC Topic: Adult

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[Clinical study on application of 3D Slicer software assisted domestic frameless stereotactic robot in biopsy of intracranial lesions].

Zhonghua wai ke za zhi [Chinese journal of surgery]
To examine the application value of 3D Slicer software assisted domestic frameless stereotactic robot in biopsy of intracranial lesions. A retrospective analysis was performed on 80 patients who admitted consecutively and underwent intracerebral le...

A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation study.

The Lancet. Digital health
BACKGROUND: One challenge in the field of in-vitro fertilisation is the selection of the most viable embryos for transfer. Morphological quality assessment and morphokinetic analysis both have the disadvantage of intra-observer and inter-observer var...

Robot-assisted modified bilateral dismembered V-shaped flap pyeloplasty for ureteropelvic junction obstruction in horseshoe kidney using KangDuo-Surgical-Robot-01 system.

International braz j urol : official journal of the Brazilian Society of Urology
PURPOSE: Horseshoe kidney (HSK) is the most common renal fusion anomaly, occurring in 0.25% of the population (1). It presents technical obstacles to pyeloplasty for ureteropelvic junction obstruction (UPJO) despite robotic assistance (2, 3). KangDuo...

[Case-control study on robot-assisted core decompression and conventional core decompression for early necrosis of femoral head].

Zhongguo gu shang = China journal of orthopaedics and traumatology
OBJECTIVE: To compare clinical effect of robot-assisted core decompression and conventional core decompression in treating ARCO Ⅰ stage necrosis of femoral head.

Machine learning models predicting undertriage in telephone triage.

Annals of medicine
BACKGROUND: Undertriaged patients have worse outcomes than appropriately triaged patients. Machine learning provides better triage prediction than conventional triage in emergency departments, but no machine learning-based undertriage prediction mode...

Validation of a Deep Learning-based Automatic Detection Algorithm for Measurement of Endotracheal Tube-to-Carina Distance on Chest Radiographs.

Anesthesiology
BACKGROUND: Improper endotracheal tube (ETT) positioning is frequently observed and potentially hazardous in the intensive care unit. The authors developed a deep learning-based automatic detection algorithm detecting the ETT tip and carina on portab...

Machine Learning-Based Prediction of Elevated PTH Levels Among the US General Population.

The Journal of clinical endocrinology and metabolism
CONTEXT: Although elevated parathyroid hormone (PTH) levels are associated with higher mortality risks, the evidence is limited as to when PTH is expected to be elevated and thus should be measured among the general population.

Prospective Validation of a Machine Learning Model for Low-Density Lipoprotein Cholesterol Estimation.

Laboratory medicine
OBJECTIVE: We aim to prospectively validate a previously developed machine learning algorithm for low-density lipoprotein cholesterol (LDL-C) estimation.

Artificial Intelligence-Based Identification of Normal Chest Radiographs: A Simulation Study in a Multicenter Health Screening Cohort.

Korean journal of radiology
OBJECTIVE: This study aimed to investigate the feasibility of using artificial intelligence (AI) to identify normal chest radiography (CXR) from the worklist of radiologists in a health-screening environment.

Development and Validation of a Deep Learning Model for Predicting Treatment Response in Patients With Newly Diagnosed Epilepsy.

JAMA neurology
IMPORTANCE: Selection of antiseizure medications (ASMs) for epilepsy remains largely a trial-and-error approach. Under this approach, many patients have to endure sequential trials of ineffective treatments until the "right drugs" are prescribed.