AIMC Topic: Prognosis

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End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study.

The Lancet. Digital health
BACKGROUND: Precise prognosis prediction in patients with colorectal cancer (ie, forecasting survival) is pivotal for individualised treatment and care. Histopathological tissue slides of colorectal cancer specimens contain rich prognostically releva...

Machine Learning-derived Multi-omics Prognostic Signature of Pyroptosis-related lncRNA with Regard to ZKSCAN2-DT and Tumor Immune Infiltration in Colorectal Cancer.

Combinatorial chemistry & high throughput screening
BACKGROUND: Colorectal cancer (CRC) has become the most prevalent gastrointestinal malignant tumor, ranking third (10.2%) in incidence and second (9.2%) in death among all malignancies globally. The most common histological subtype of CRC is colon ad...

Design of an interface to communicate artificial intelligence-based prognosis for patients with advanced solid tumors: a user-centered approach.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To design an interface to support communication of machine learning (ML)-based prognosis for patients with advanced solid tumors, incorporating oncologists' needs and feedback throughout design.

Machine learning and deep learning predictive models for long-term prognosis in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis.

The Lancet. Digital health
BACKGROUND: Machine learning and deep learning models have been increasingly used to predict long-term disease progression in patients with chronic obstructive pulmonary disease (COPD). We aimed to summarise the performance of such prognostic models ...

[Cox model analysis of curative effect and prognostic factors of oral robot-assisted RPLN dissection for head and neck malignancies].

Shanghai kou qiang yi xue = Shanghai journal of stomatology
PURPOSE: To investigate the efficacy and prognostic factors of oral robot-assisted retropharyngeal lymph node (RPLN) dissection in the treatment of head and neck malignancies.

[Methodology and progress in adjusting time-dependent covariates in clinical prediction models].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
Adjusting time-dependent covariates into prediction models may help improve model performance and expand clinical applications. The methodology of handling time-dependent covariates is limited in traditional regression strategies (i.e., landmark mode...

[Application of machine learning in clinical predictive models for infectious diseases: a review].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control
Infectious diseases are one of the major threats to global public health. Inconvenience of diagnosis and treatment frequently causes misdiagnosis, missing diagnosis or overtreatment, resulting in serious clinical outcomes. As an important branch of a...

Overcoming the challenges to implementation of artificial intelligence in pathology.

Journal of the National Cancer Institute
Pathologists worldwide are facing remarkable challenges with increasing workloads and lack of time to provide consistently high-quality patient care. The application of artificial intelligence (AI) to digital whole-slide images has the potential of d...

Interhemispheric connections in the maintenance of language performance and prognosis prediction: fully connected layer-based deep learning model analysis.

Neurosurgical focus
OBJECTIVE: Language-related networks have been recognized in functional maintenance, which has also been considered the mechanism of plasticity and reorganization in patients with cerebral malignant tumors. However, the role of interhemispheric conne...

Radiomics in colorectal cancer patients.

World journal of gastroenterology
The main therapeutic options for colorectal cancer are surgical resection and adjuvant chemotherapy in non-metastatic disease. However, the evaluation of the overall adjuvant chemotherapy benefit in patients with a high risk of recurrence is challeng...