AIMC Topic: Male

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[Lateral Port Site Hernia Following Robot Assisted Laparoscopic Radical Prostatectomy : A Case Report and Literature Review].

Hinyokika kiyo. Acta urologica Japonica
The patient was a 69-year-old man with localized cT1cN0M0 prostate cancer, who underwent robotassisted laparoscopic prostatectomy (RALP). The operation time was 188 minutes, blood loss was 300 ml, including urine, and no intraoperative complications ...

[Artificial intelligence: the inscrutability of algorithms.].

Recenti progressi in medicina
The use of artificial intelligence radically changes the role of the doctor and his/her relationship with the patient, which becomes in fact a three-way relationship: artificial intelligence-doctor-patient, in which the first component is able to hea...

Robot-assisted laparoscopic resection of a pelvic solitary fibrous tumor.

The Journal of international medical research
Solitary fibrous tumor (SFT) is a rare soft tissue neoplasm of mesenchymal origin. SFT is most commonly located in the thoracic cavity (in approximately 80% of cases), but can also develop rarely in the pelvis. A 47-year-old man presented to our hosp...

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

JAMA psychiatry
IMPORTANCE: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to yo...

The Auto-eFACE: Machine Learning-Enhanced Program Yields Automated Facial Palsy Assessment Tool.

Plastic and reconstructive surgery
BACKGROUND: Facial palsy assessment is nonstandardized. Clinician-graded scales are limited by subjectivity and observer bias. Computer-aided grading would be desirable to achieve conformity in facial palsy assessment and to compare the effectiveness...

Early prediction of mortality risk among patients with severe COVID-19, using machine learning.

International journal of epidemiology
BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 infection, has been spreading globally. We aimed to develop a clinical model to predict the outcome of patients with severe COVID-19 infection ...

Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets.

Lancet (London, England)
BACKGROUND: The accuracy of current prediction tools for ischaemic and bleeding events after an acute coronary syndrome (ACS) remains insufficient for individualised patient management strategies. We developed a machine learning-based risk stratifica...