AIMC Topic: Male

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Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

American journal of respiratory and critical care medicine
Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and improve long-term outcomes. To develop a model to predict a future diagnosis of lung cancer on the basi...

Transanal Minimally Invasive Surgery: A Useful Technique That Continues to Evolve.

Surgical technology international
Colorectal cancer remains the 3rd most common cancer diagnosed among men and women in the United States. With improved screening, premalignant rectal lesions and rectal cancers are being detected at earlier stages. In addition, the use of neoadjuvant...

Electrocardiogram screening for aortic valve stenosis using artificial intelligence.

European heart journal
AIMS: Early detection of aortic stenosis (AS) is becoming increasingly important with a better outcome after aortic valve replacement in asymptomatic severe AS patients and a poor outcome in moderate AS. We aimed to develop artificial intelligence-en...

Quantitative Assessment of Fundus Tessellated Density and Associated Factors in Fundus Images Using Artificial Intelligence.

Translational vision science & technology
PURPOSE: This study aimed to quantitative assess the fundus tessellated density (FTD) and associated factors on the basis of fundus photographs using artificial intelligence.

[Needle Lost during Robot-Assisted Laparoscopic Radical Prostatectomy : A Case Report].

Hinyokika kiyo. Acta urologica Japonica
A 66-year-old man, who presented with prostate cancer, underwent robot-assisted laparoscopic radical prostatectomy. During surgery, a suture needle was lost after an assistant surgeon removed it from the AirSealĀ® access port. We were not able to find...

Artificial neural network prediction of same-day discharge following primary total knee arthroplasty based on preoperative and intraoperative variables.

The bone & joint journal
AIMS: This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA).

Radiogenomic and Deep Learning Network Approaches to Predict Mutation from Radiotherapy Plan CT.

Anticancer research
BACKGROUND/AIM: We aimed to investigate the role of radiogenomic and deep learning approaches in predicting the KRAS mutation status of a tumor using radiotherapy planning computed tomography (CT) images in patients with locally advanced rectal cance...

Predictive Risk Models for Wound Infection-Related Hospitalization or ED Visits in Home Health Care Using Machine-Learning Algorithms.

Advances in skin & wound care
OBJECTIVE: Wound infection is prevalent in home healthcare (HHC) and often leads to hospitalizations. However, none of the previous studies of wounds in HHC have used data from clinical notes. Therefore, the authors created a more accurate descriptio...

Prediction of Prolonged Opioid Use After Surgery in Adolescents: Insights From Machine Learning.

Anesthesia and analgesia
BACKGROUND: Long-term opioid use has negative health care consequences. Patients who undergo surgery are at risk for prolonged opioid use after surgery (POUS). While risk factors have been previously identified, no methods currently exist to determin...