Ankit Kalucha

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Ankit Kalucha

Ankit Kalucha

@Ankitowledge

Easing oncology outcomes decision making

India Katılım Aralık 2023
457 Takip Edilen53 Takipçiler
Enrique Grande
Enrique Grande@drenriquegrande·
⚡️ Final THOR-2 readout: oral erdafitinib improved RFS vs intravesical chemo in FGFR3/2-altered high-risk papillary NMIBC and showed durable CRs in CIS and intermediate-risk cohorts. Safety in line with FGFR inhibitors. Despite early stop/small N, it reinforces FGFR-targeted strategies in NMIBC and supports intravesical TAR-210. #BladderCancer sciencedirect.com/science/articl…
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ASCO
ASCO@ASCO·
NEW ASCO Guidelines Assistant tool leverages Google Cloud Vertex AI platform & Gemini models, enabling oncology clinicians to quickly access evidence-based clinical guidelines.
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ONCO BRUNO
ONCO BRUNO@brunolarvol·
Does it mean ~100k oncologists globally ? That’s the number I used informally. @Ankitowledge
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Giannis Mountzios
Giannis Mountzios@g_mountzios·
Immune cell effector-associated neurotoxicity syndrome (ICANS) is a less well understood entity related to cytokine disruption of BBB and comprising diverse neurological symptoms. ICANS was rare (<10%) and no ICANS 3 or more was observed. (pic from Sands Cancer 2024) 🧵12/15
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Joachim Schork
Joachim Schork@JoachimSchork·
Principal Component Analysis (PCA) is a powerful tool for dimensionality reduction, used to simplify complex data sets while retaining their most important features. It transforms the original variables into a new set of uncorrelated variables called principal components. These components capture the maximum variance in the data, making it easier to analyze and visualize. Key Points: ✔️ Simplifies data sets by reducing the number of variables. ✔️ Helps in identifying patterns and insights. ✔️ Improves the performance of machine learning models. ❌ May result in loss of some information. ❌ Interpretation of components can be challenging. Practical Implementation: 🔹 R: Use prcomp() from the stats package for performing PCA. 🔹 Python: Use PCA from the sklearn.decomposition module for PCA implementation. For a detailed step-by-step tutorial on PCA, including practical examples, check out my tutorials created in collaboration with Paula Villasante Soriano & @Cansu_SG. Article: statisticsglobe.com/principal-comp… Video: youtube.com/watch?v=DngS4L… Furthermore, I have created an extensive introduction to PCA, which explains the theoretical concepts of PCA as well as how to apply it in R programming. More info: statisticsglobe.com/online-course-… #database #DataScience #DataAnalytics #Rpackage #RStats #R #StatisticalAnalysis
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Ankit Kalucha
Ankit Kalucha@Ankitowledge·
SWOT by Deep Research. Potential SOC SERENA 6.
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Ankit Kalucha
Ankit Kalucha@Ankitowledge·
Generative Reward Models Self-Taught Reasoning (STAR) in AI Training for cancer clinical trials
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Ankit Kalucha
Ankit Kalucha@Ankitowledge·
Mixture-of-experts Concepts
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Arndt Vogel
Arndt Vogel@ArndtVogel·
Comparison of 1st chemotherapy in unresectable locally advanced or metastatic #PDAC @TheLancetOncol doi.org/10.1016/S1470-… 🔎systematic review & Bayesian network meta-analysis, 79 trials, 22 168 pts 👉NALIRIFOX & FOLFIRINOX may be the preferred options if feasible @myESMO
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Arndt Vogel
Arndt Vogel@ArndtVogel·
LEAP-012: A Phase 3 Study of Lenvatinib Plus Pembrolizumab Plus Transarterial Chemoembolization for Intermediate-Stage HCC @ILCA 👉meaningful improvement in ORR & PFS 👉OS immature 🧐TACE + ICI based💊is a great option for downsizing & disease control in HCC @myESMO @EASLedu
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MJosé Juan
MJosé Juan@mjuanfi81·
PSA screening guidelines. Start age?Stop age?Frequency? Debate is served. doi:10.1001/jamaoncol.2024.3909
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