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Cohort Studies

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Ovarian Cancer-Self Assessment: An Innovation for Early Detection and Risk Assessment of Ovarian Cancer.

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE: The modality to detect ovarian cancer at an early stage is very limited. Early diagnosis determines the prognosis. This study aimed to develop a risk assessment tool for early detection of ovarian cancer using artificial intelligence. To a...

Performance of deep learning in the detection of intracranial aneurysm: A systematic review and meta-analysis.

European journal of radiology
PURPOSE: Early detection and diagnosis of intracranial aneurysms (IAs) are particularly critical. Deep learning models (DLMs) are now widely used in the diagnosis of various diseases. Different DLMs have been developed to detect IAs. However, the ove...

Natural Language Processing to Improve Prediction of Incident Atrial Fibrillation Using Electronic Health Records.

Journal of the American Heart Association
Background Models predicting atrial fibrillation (AF) risk, such as Cohorts for Heart and Aging Research in Genomic Epidemiology AF (CHARGE-AF), have not performed as well in electronic health records. Natural language processing (NLP) may improve mo...

The Impact of Gleason Grade 3 as a Predictive Factor for Biochemical Recurrence after Robot-Assisted Radical Prostatectomy: A Retrospective Multicenter Cohort Study in Japan (The MSUG94 Group).

Medicina (Kaunas, Lithuania)
: This study's objective was to examine patients treated with robot-assisted radical prostatectomy (RARP) for intermediate-risk prostate cancer (IR-PCa), and to identify preoperative risk factors for biochemical recurrence (BCR) in these patients in ...

A Machine Learning Model for Predicting Mortality within 90 Days of Dialysis Initiation.

Kidney360
BACKGROUND: The first 90 days after dialysis initiation are associated with high morbidity and mortality in end-stage kidney disease (ESKD) patients. A machine learning-based tool for predicting mortality could inform patient-clinician shared decisio...

Continuously sutured versus linear-stapled anastomosis in robot-assisted hybrid Ivor Lewis esophageal surgery following neoadjuvant chemoradiotherapy: a single-center cohort study.

Surgical endoscopy
BACKGROUND: Esophageal cancer surgery is technically highly demanding. During the past decade robot-assisted surgery has successfully been introduced in esophageal cancer treatment. Various techniques are being evaluated in different centers. In part...

Explainable machine learning for real-time deterioration alert prediction to guide pre-emptive treatment.

Scientific reports
The Electronic Medical Record (EMR) provides an opportunity to manage patient care efficiently and accurately. This includes clinical decision support tools for the timely identification of adverse events or acute illnesses preceded by deterioration....

Dental anomaly detection using intraoral photos via deep learning.

Scientific reports
Children with orofacial clefting (OFC) present with a wide range of dental anomalies. Identifying these anomalies is vital to understand their etiology and to discern the complex phenotypic spectrum of OFC. Such anomalies are currently identified usi...

Electronic Health Record-Based Deep Learning Prediction of Death or Severe Decompensation in Heart Failure Patients.

JACC. Heart failure
BACKGROUND: Surgical mechanical ventricular assistance and cardiac replacement therapies, although life-saving in many heart failure (HF) patients, remain high-risk. Despite this, the difficulty in timely identification of medical therapy nonresponde...

Generation of Individualized Synthetic Data for Augmentation of the Type 1 Diabetes Data Sets Using Deep Learning Models.

Sensors (Basel, Switzerland)
In this paper, we present a methodology based on generative adversarial network architecture to generate synthetic data sets with the intention of augmenting continuous glucose monitor data from individual patients. We use these synthetic data with t...