Results 181 to 190 of about 180,771 (310)

Clinical periodontal diagnosis

open access: yesPeriodontology 2000, EarlyView., 2023
Abstract Periodontal diseases include pathological conditions elicited by the presence of bacterial biofilms leading to a host response. In the diagnostic process, clinical signs such as bleeding on probing, development of periodontal pockets and gingival recessions, furcation involvement and presence of radiographic bone loss should be assessed prior ...
Giovanni E. Salvi   +5 more
wiley   +1 more source

A Milky Mystery: Chylothorax Unmasking Non-Hodgkin Lymphoma. [PDF]

open access: yesCureus
Tangutoori S   +6 more
europepmc   +1 more source

An unusual presentation of non-Hodgkin lymphoma: Cardiac involvement

open access: diamond, 2010
Rhizlane Belbaraka   +3 more
openalex   +1 more source

Prognostic significance of pretransplant 18F‐FDG PET/CT metrics in relapsed/refractory diffuse large B‐cell lymphoma with partial response to salvage chemotherapy prior to autologous stem cell transplantation

open access: yesBritish Journal of Haematology, EarlyView.
Summary Relapsed/refractory diffuse large B‐cell lymphoma (R/R DLBCL) patients with partial response (PR) to salvage chemotherapy show heterogeneous outcomes after autologous stem cell transplantation (ASCT). Current visual positron emission tomography (PET) assessment inadequately identifies patients likely to benefit from transplantation.
Minseung Suh   +15 more
wiley   +1 more source

A peculiar case of primary lymphoma of pancreas: A rare presentation of Hodgkin lymphoma. [PDF]

open access: yesOncoscience
Mohiuddin O   +5 more
europepmc   +1 more source

HERV-K Envelope Induce a Humoral Response in Non-Hodgkin Lymphoma Patients. [PDF]

open access: yesCurr Microbiol
Cossu I   +7 more
europepmc   +1 more source

Artificial intelligence for risk assessment and outcome prediction in malignant haematology

open access: yesBritish Journal of Haematology, EarlyView.
Machine learning models allow for dynamic and scalable risk stratification and outcome prediction. Different modalities of data such as electronic health records, patient genetics or laboratory results can be used as input. ML models autonomously select features weighing their prognostic value. Methods of model explainability in feature selection allow
Jan‐Niklas Eckardt   +3 more
wiley   +1 more source

Home - About - Disclaimer - Privacy