AIMC Topic: Male

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Dysfunctional Beliefs and Attitudes about Sleep-6 (DBAS-6): Data-driven shortened version from a machine learning approach.

Sleep medicine
BACKGROUND: The Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16) is a widely used self-report instrument for identifying sleep-related cognition. However, its length can be cumbersome in clinical practice. This study aims to develop a ...

Machine learning for predicting liver and/or lung metastasis in colorectal cancer: A retrospective study based on the SEER database.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
OBJECTIVE: This study aims to establish a machine learning (ML) model for predicting the risk of liver and/or lung metastasis in colorectal cancer (CRC).

Machine-learning-based risk assessment tool to rule out empirical use of ESBL-targeted therapy in endemic areas.

The Journal of hospital infection
BACKGROUND: Antimicrobial stewardship focuses on identifying patients who require extended-spectrum beta-lactamase (ESBL)-targeted therapy. 'Rule-in' tools have been researched extensively in areas of low endemicity; however, such tools are inadequat...

Predictive value of magnetic resonance imaging diffusion parameters using artificial intelligence in low-and intermediate-risk prostate cancer patients treated with stereotactic ablative radiotherapy: A pilot study.

Radiography (London, England : 1995)
INTRODUCTION: To investigate the predictive value of the pre-treatment diffusion parameters of diffusion-weighted magnetic resonance imaging (DW-MRI) using artificial intelligence (AI) for prostate-specific antigen (PSA) response in patients with low...

Ultrasound-based radiomics machine learning models for diagnosing cervical lymph node metastasis in patients with non-small cell lung cancer: a multicentre study.

BMC cancer
BACKGROUND: Cervical lymph node metastasis (LNM) is an important prognostic factor for patients with non-small cell lung cancer (NSCLC). We aimed to develop and validate machine learning models that use ultrasound radiomic and descriptive semantic fe...

Efficient diagnosis of psoriasis and lichen planus cutaneous diseases using deep learning approach.

Scientific reports
The tendency of skin diseases to manifest in a unique and yet similar appearance, absence of enough competent dermatologists, and urgency of diagnosis and classification on time and accurately, makes the need of machine aided diagnosis blatant. This ...

Predicting postoperative rehemorrhage in hypertensive intracerebral hemorrhage using noncontrast CT radiomics and clinical data with an interpretable machine learning approach.

Scientific reports
In hypertensive intracerebral hemorrhage (HICH) patients, while emergency surgeries effectively reduce intracranial pressure and hematoma volume, their significant risk of causing postoperative rehemorrhage necessitates early detection and management...

Personalised prediction of maintenance dialysis initiation in patients with chronic kidney disease stages 3-5: a multicentre study using the machine learning approach.

BMJ health & care informatics
BACKGROUND: Optimal timing for initiating maintenance dialysis in patients with chronic kidney disease (CKD) stages 3-5 is challenging. This study aimed to develop and validate a machine learning (ML) model for early personalised prediction of mainte...