Is AI replacing the work of skilled radiologists? They give us their thoughts | The-14 Radiologists explain how AI assists medical imaging without replacing experts yet, improving detection and workflow while raising new questions about skills

Is AI replacing the work of skilled radiologists? They give us their thoughts
#AI #Radiology #HealthcareAI #MedicalImaging #AIImpact #HealthTech #Innovation #Doctors #DigitalHealth #TechAnalysis #TechInHealthcare #WorkplaceTech #FutureMedicine #MedicalAI
the-14.com/is-ai-replac...

📸 Computational photography and the confluence of vision and graphics #ComputationalPhotography #DigitalImaging #NeuralRendering
🧬 Biomedical image processing and analysis #MedicalImaging #MedicalAI
📱 Applications (e.g., biometrics, document analysis, etc.) #BiometricSecurity

AI in Radiomics Using Imaging Data to Predict Treatment Response Introduction Artificial Intelligence (AI) has emerged as a powerful tool in healthcare, advancing medical imaging and precision diagnostics. A particularly promising application is radiomics, a ...

AI in Radiomics Using Imaging Data to Predict Treatment Response
www.ekascloud.com/our-blog/ai-...
#AIinHealthcare #Radiomics #MedicalImaging #ArtificialIntelligence #HealthTech #MedicalAI #DigitalHealth #FutureOfMedicine #HealthcareInnovation #AITechnology #Data

AI Is Quietly Taking Over Medicine. That Is Both Wonderful and Slightly Terrifying. From wearables and AI therapists to echocardiography models, drug design engines, and biotech agent swarms, healthcare is becoming the…

AI is moving into medicine fast.

Health-data analysis, ultrasound models, drug design engines, biotech agent swarms, and AI therapy are making healthcare one of the most important AI battlegrounds.

go.abvx.xyz/kcd3lt

#MedicalAI #DigitalHealth #AI

🏥 AI is transforming healthcare technology.

From medical AI apps to healthtech SaaS platforms, intelligent systems can automate analysis, improve workflows, and support healthcare innovation.

Explore AI healthcare solutions 👇

go.fiverr.com/visit/?bta=2...

#HealthTech #MedicalAI #AIsoftware #SaaS

AI is transforming cancer research, diagnostics, and precision medicine.

Explore AI healthcare innovation at AIIM-2026

2026 | Hybrid Event

🔗 ai-medicalcongress.com

#ArtificialIntelligence #AIinHealthcare #CancerResearch #Oncology #MedicalAI #MachineLearning #HealthTech

Comparative Study of CNN Architectures for Brain Tumor Classification Using MRI: Exploring GradCAM for Visualizing CNN Focus
www.mdpi.com/2673-4591/83...

By Areli Chinga et al.
From the CITIIC 2023 Congress

#AIinHealthcare #DeepLearning #MedicalAI

Be part of AIIM 2026 – 2nd Edition of AI in Medicine!

May 4–5, 2026 | Boston, MA, USA | Attend In-Person or Online

Meet global leaders advancing AI in healthcare innovation.

🔗 ai-medicalcongress.com

#AIinMedicine #MedicalAI #HealthcareAI #DigitalHealth #PrecisionMedicine

FDA 510(k) or CE marking for medical AI isn't just about labels. Your entire data pipeline needs to be audit-ready.
iMerit combines clinical expertise with validated processes to move models into clinical use:
imerit.net/domains/medi...

#MedicalAI #FDA #HealthTech #AICompliance

Factors for Patient Trust and Acceptance of Medical Artificial Intelligence This survey study examines the associations of patient trust in and choice of medical scenarios involving artificial intelligence with receiving information on governance mechanisms, clinician presenc...

What influences patient trust in & choice of medical AI encounters?
In a conjoint survey experiment, 3000k folks picked hypothetical visits.
AI performance, clinician presence, & governance all mattered.

#Medsky #MedicalAI
jamanetwork.com/journals/jam...
@jamanetworkopen.com @kaytesb.bsky.social

Abstract submissions are still open! Join AIIM-2026 by Sciinov on May 04–05, 2026 in Boston and present your research.

🔗 ai-medicalcongress.com/abstract-sub...

#AIinMedicine #HealthcareAI #MedicalAI #DigitalHealth #HealthTech #AIConference

Can one AI analyze all medical scans? MedVersa shows promise across multiple imaging tasks esearchers developed MedVersa, a generalist multimodal AI model trained on tens of millions of medical imaging instances to perform diverse radiology tasks within a single framework. The model matched...

🩻 Can one AI analyze ALL medical scans? MedVersa, trained on 29M+ images, delivers human-comparable reports in many cases & unifies tasks across X-ray, CT, and MRI.
www.news-medical.net/news/2026030... #MedicalAI #Radiology @ai.nejm.org

This week at #AIMMLab 🧠🔬

Keishi Suzuki presented: Distribution-Aware Multi-Stage Transfer Learning for Mammography Using Biomedical Vision–Language Models.

Exploring how foundation models + transfer learning can improve robustness of #medicalAI across imaging datasets.

Trivia hosted by Jusleen! 🎉

Wiley licensed Cochrane to a platform that runs on advertising and has a history of pay-to-play misinformation. Think Google, but for doctors.

If your licensing partner makes money from ads, what happens to the content?

www.the-geyser.com/openevidence...

#MedicalAI #ResearchIntegrity

🧵 The Rule of 3s in Sepsis

1️⃣ Fluids 💧
Restore perfusion.
Crystalloids first. Don’t wait.

2️⃣ Antibiotics 💊

Broad‑spectrum.
Within the first hour.
Every minute counts.

3️⃣ Oxygen 🌬️
Support tissue oxygenation.
Prevent organ failure.

#medicalcontent #clinicalpearls #medicalAI #healthtech

AI Ultrasound for Testicular Cancer: Can Smart Scans Catch Trouble Earlier? AI-powered ultrasound revolutionizes testicular cancer detection, helping doctors catch lumps earlier and more accurately for better outcomes.

Early detection is everything in testicular cancer.

With AI-enhanced ultrasound, we’re moving from “detecting when visible” to “detecting when subtle.”

Read more:
🔗 jaykumar41.blogspot.com/2026/03/ai-u...

#AIinHealthcare #MedicalAI #Oncology #HealthTech

Join the Artificial Intelligence in Medicine Conference (AIIM 2026)
📅 May 04–05, 2026 | 📍 Boston, USA | 🌐 Hybrid Event

🔗 ai-medicalcongress.com

#AIIM2026 #AIinHealthcare #HealthTech #MedicalAI

AI is transforming healthcare — be part of the revolution at #AIIM2026

May 04–05, 2026
Boston + Online

🔗 Learn more: ai-medicalcongress.com

🎟️ Register: ai-medicalcongress.com/registration

#ArtificialIntelligence #HealthTech #MedicalAI #FutureOfHealthcare

Regulatory Validation for Arthritis AI Diagnosis and Treatment | Case Study with iMerit YouTube video by iMerit

MedTech AI for arthritis diagnosis & custom hip replacements met FDA 510(k) validation with iMerit.
▪️5,000+ CT/MRI scans
▪️99% annotation quality
▪️98.8% diagnostic accuracy
▪️72% cost savings

Watch: www.youtube.com/watch?v=aSpg...
#MedicalAI #RegulatoryAI #RadiologyAI #FDA510k #iMerit

Call for Abstracts – 2nd Round Now Open!

Join AIIM 2026: Artificial Intelligence in Medicine
May 04–05, 2026 | Boston, USA

Present your research, shape healthcare AI future!

Submit here: ai-medicalcongress.com/submit-abstr...

#AIinMedicine #MedicalAI #DigitalHealth #HealthTech

Join AI and biology leaders this June at the Wellcome Genome Campus🧬

🗓️Dates: 8–10 June
#AIxBio26 explores how AI is transforming human biology and medicine.

Need financial support to attend?
Apply for a bursary by March 16 ➡️ bit.ly/3OzMULQ

#AIinBiology #MachineLearning #Biotech #MedicalAI 🤖

ture of medicine.

Join the 2nd Edition: Artificial Intelligence in Medicine (AIIM-2026)
📅 May 04–05, 2026 | 📍 Boston, USA
🔗 ai-medicalcongress.com

#AIinMedicine #HealthcareAI #MedicalAI #DigitalHealth #HealthTech

"Warm Hands" Palpation: 500k Yen. Doctor Visit is "Manned Mission"

Free AI diagnosis makes human exams a luxury. Patients weep at the touch; stethoscope tattoos trend.

alt.andpaper.net/en/articles/20260301-man...

#MedicalAI #MannedMission

Mid-term registration ends Feb 28, 2026!

Don’t miss AIIM 2026 – Artificial Intelligence in Medicine

Boston | 🌐 Hybrid
May 4–5, 2026

Secure your spot today 👇
ai-medicalcongress.com/registrations/

#AIIM2026 #HealthcareInnovation #DigitalHealth #AIConference #HealthTech #MedicalAI #Boston

Retrieval-Augmented Generation for Medical Question Answering on a Heart Failure Dataset: Performance Analysis Background: The integration of retrieval-augmented generation (RAG) systems into the domain of medical question-answering (QA) presents a significant opportunity to enhance the effectiveness and accuracy of clinical support systems. Objective: This study aimed to explore the design choices within the RAG framework and the use of large language model (LLM) classifiers to optimize medical QA systems, enhancing response quality for patient and caregiver queries of varying risk levels. Methods: In total, we curated a dataset of 109 patient and caregiver questions related to heart failure (HF)—categorized into answerable (direct, fact-based queries), helpful deferral (general guidance or lifestyle advisory queries), and nonanswerable (out-of-scope or high-risk and medical intervention queries) types—along with relevant documents and a target answer for each question from the website . Applying a system architecture leveraging RAG with a structured query taxonomy and robust classification mechanisms, this paper provided an empirical assessment for medical QA on a HF dataset and introduced a QA system pipeline design, providing a foundation for extended application across various medical fields. Specifically, we evaluated design choices in the initial retrieval stage of RAG and their impact on performance. We assessed final answer quality from the generation stage using popular passage scoring methods for QA, such as Recall-Oriented Understudy for Gisting Evaluation (ROUGE), BERTScore, and Intersection over Union score. Results: The pipeline first uses an LLM-based classifier, achieving 65% accuracy for answerable and helpful deferral queries and 100% accuracy for identifying nonanswerable queries. In information retrieval, the BioMedical Contrastive Pre-trained Transformers (MedCPT) cross encoder performed best as a dense retrieval method, delivering an average of 93% recall @ 7 through ranked relevance scores to obtain the top documents with recall @ k denoting recall computed over the top-k retrieved items. For further retrieving snippets from such documents, its average performance was 72.5% for sentence-level snippets and 83% for paragraph-level snippets. A second LLM-based classifier, used to refine the generated responses, resulted in an overall reduction in ROUGE-1 recall by 13% and Bidirectional Encoder Representations from Transformers (BERT) precision by 11%. However, Intersection over Union scores, or the overlap between “gold answers” and system answers, increased by 24%, demonstrating enhanced alignment with ground truth responses. This also indicates the system’s improved ability to generate concise and accurate medical responses. Conclusions: The implementation of a structured RAG framework paired with LLM classifiers for medical QA introduces a promising avenue for enhancing clinical decision support systems. By systematically analyzing the impact of query taxonomy, retrieval configurations, and response strategies, this approach clarifies the relative importance of each component within the medical RAG system using a HF dataset. Our findings provide actionable guidance on optimal design choices for maximizing retrieval and response accuracy; thus, informing the development of robust, scalable medical QA systems.

JMIR Formative Res: Retrieval-Augmented Generation for Medical Question Answering on a Heart Failure Dataset: Performance Analysis #MedicalAI #HeartFailure #DigitalHealth #HealthTech #ArtificialIntelligence

AI is transforming the future of healthcare!
Join AIIM 2026 – Artificial Intelligence in Medicine in Boston, USA

May 04–05, 2026
Mid Registration ends Feb 28, 2026

🔗 Register: ai-medicalcongress.com/registrations/

#AIinMedicine #HealthcareAI #MedicalAI #DigitalHealth #AIConference

In a Straight Arrow News article, Sina Bari, MD, shares his perspective on how AI can reduce the burden of clinician documentation and help restore patient trust in healthcare.

Read more: bit.ly/4qX1AlI
#HealthcareAI #MedicalAI

Episode 7 is where we stop celebrating long enough to ask: who benefits? AI bias, energy costs & the equity gap. #AIInnovationsUnleashed #AlgorithmicBias #MedicalAI 🧬
www.aiinnovationsunleashed.com/?p=3785

AI is transforming healthcare!

Join AIIM 2026 – Artificial Intelligence in Medicine
May 04–05, 2026 | Boston, USA

Submit your abstract by Feb 23, 2026 (2nd round closing soon!)

🔗 ai-medicalcongress.com/abstract-sub...

#HealthcareAI #DigitalHealth #HealthTech #MedicalAI #PrecisionMedicine

Docs are eyeing generative AI to boost diagnoses, streamline workflows, and reshape patient care. Curious how large language models could become the next medical tech must‑have? Dive into the Pitt’s deep dive. #GenerativeAI #MedicalAI #PatientCare

🔗 aidailypost.com/news/pitt-ex...