AIMC Topic: Treatment Outcome

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Characterizing immune profiles in hepatocellular carcinoma patients benefiting from pembrolizumab and lenvatinib using machine learning.

BMC cancer
BACKGROUND: Combination immunotherapies, such as pembrolizumab plus lenvatinib (PL), are commonly used in treatment for unresectable hepatocellular carcinoma (uHCC). However, it remains challenging to predict which patients will benefit from this the...

Exploring the therapeutic effects of continuous kidney replacement therapy in patients with severe acidosis using deep learning-based causal inference.

Scientific reports
Continuous kidney replacement therapy (CKRT) is an essential treatment for uncontrolled severe metabolic acidosis. However, CKRT can increase workload and lead to complications, thus necessitating its selective application to patients who stand to be...

Machine learning detects hidden treatment response patterns only in the presence of comprehensive clinical phenotyping.

PloS one
Inferential statistics traditionally used in clinical trials can miss relationships between clinical phenotypes and treatment responses. We simulated a randomised clinical trial to explore how gradient boosting (XGBoost) machine learning compares wit...

Efficacy and safety of platelet-rich plasma injections for the treatment of knee osteoarthritis: a systematic review and meta-analysis of randomized controlled trials.

European journal of medical research
INTRODUCTION: Knee osteoarthritis (KOA) is a prevalent degenerative joint disorder affecting a significant portion of the elderly population. Despite the availability of various non-surgical and pharmacological treatments, their effectiveness is ofte...

Association between lipid profiles and early clinical outcomes in acute ischemic stroke: a single-center cohort study in the Chinese population.

BMC neurology
BACKGROUND: The clinical significance and contribution of the lipid profile in atherosclerosis are well established. However, further investigation is needed in stroke patients, particularly regarding apolipoprotein B100 (ApoB100), a novel non-tradit...

Neurophysiological mechanisms and predictive modeling of SSRI treatment response in depression disorder based on multidimensional EEG features.

Journal of affective disorders
BACKGROUND: Depression exhibits significant heterogeneity in antidepressant treatment response. This study aimed to develop an Electroencephalography (EEG)-based machine learning model integrating multidimensional features to predict selective seroto...

Computational pathology approach for assessment of prognosis and immunotherapy response in pan-gastrointestinal cancer.

Journal of translational medicine
BACKGROUND: Current cancer staging methods cannot accurately predict survival outcomes and therapeutic benefits in cancer patients. Digital pathomics, a rapidly evolving field, holds significant potential to revolutionize disease evaluation.

Novel electroencephalographic biomarkers for the prediction of responders to an experimental glutamatergic agent in patients with schizophrenia.

Translational psychiatry
All medications currently used to treat schizophrenia, which exert their therapeutic effects by inhibiting dopaminergic neurotransmission, have their greatest efficacy against the positive symptoms of schizophrenia but have limited impact on negative...

Iloprost therapy achieves good clinical and radiological short and mid-term outcomes in patients with idiopathic aseptic osteonecrosis of the knee joint also in ARCO level II.

Archives of orthopaedic and trauma surgery
AIMS: The aim of this retrospective study was the evaluation of the patient-reported and radiological outcome of intravenous Iloprost therapy in the treatment of spontaneous osteonecrosis of the knee (SONK).