AIMC Topic: Treatment Outcome

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Extremity Soft Tissue Sarcoma Reconstruction Nomograms: A Clinicoradiomic, Machine Learning-Powered Predictor of Postoperative Outcomes.

JCO clinical cancer informatics
PURPOSE: The choice of wound closure modality after limb-sparing extremity soft-tissue sarcoma (eSTS) resection is fraught with uncertainty. Leveraging machine learning and clinicoradiomic data, we developed Sarcoma Reconstruction Nomograms (SARCON),...

Analysis of IPV success treatment from an AI approach.

PloS one
Intimate partner violence (IPV) is a serious social problem in Chile. Understanding the patterns of internalization and the motivations maintaining it is crucial to design optimal treatments that ensure adherence and completeness. This, in addition, ...

NeoPred: dual-phase CT AI forecasts pathologic response to neoadjuvant chemo-immunotherapy in NSCLC.

Journal for immunotherapy of cancer
BACKGROUND: Accurate preoperative prediction of major pathological response or pathological complete response after neoadjuvant chemo-immunotherapy remains a critical unmet need in resectable non-small-cell lung cancer (NSCLC). Conventional size-base...

Clinical, genetic, and sociodemographic predictors of symptom severity after internet-delivered cognitive behavioural therapy for depression and anxiety.

BMC psychiatry
BACKGROUND: Internet-delivered cognitive behavioural therapy (ICBT) is an effective and accessible treatment for mild to moderate depression and anxiety disorders. However, up to 50% of patients do not achieve sufficient symptom relief. Identifying p...

Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors.

Journal for immunotherapy of cancer
BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed the oncology treatment landscape. Despite substantial improvements for some patients, the majority do not benefit from ICIs, indicating a need for predictive biomarkers to better inform...

Inflammatory biomarkers as predictors for unlocking antidepressant efficacy: Assessing predictive value and risk stratification in major depressive disorder in a prospective longitudinal study.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) is characterized by significant heterogeneity in treatment response, with inflammation hypothesized to play a role in its pathophysiology. Peripheral inflammatory biomarkers, such as the neutrophil-to-lymph...

Mechanisms and management of self-resolving lumbar disc herniation: bridging molecular pathways to non-surgical clinical success.

Journal of orthopaedic surgery and research
Spontaneous resorption of lumbar disk herniation (LDH) presents a promising avenue for the non-surgical management of herniated disks. Here we present a 40-year-old female with severe L5/S1 herniation who experienced spontaneous resorption confirmed ...

Predicting treatment response in individuals with major depressive disorder using structural MRI-based similarity features.

BMC psychiatry
BACKGROUND: Major Depressive Disorder (MDD) is a prevalent mental health condition with significant societal impact. Structural magnetic resonance imaging (sMRI) and machine learning have shown promise in psychiatry, offering insights into brain abno...

Single-cell multimodal analysis reveals tumor microenvironment predictive of treatment response in non-small cell lung cancer.

Science advances
Non-small cell lung cancer (NSCLC) constitutes over 80% of lung cancer cases and remains a leading cause of cancer-related mortality worldwide. Despite the advent of immune checkpoint inhibitors, their efficacy is limited to 27 to 45% of patients. Id...

Using ML techniques to predict extubation outcomes for patients with central nervous system injuries in the Yun-Gui Plateau.

Scientific reports
No predictive models have been reported for tracheostomy extubation success in plateau region rehabilitation departments. Hence, the primary objective of this retrospective study was to evaluate the predictive capabilities of different models for ext...