Tuberculosis

Deep learning extracts MoA-specific signatures from high-throughput images of chemically and genetically perturbed Corynebacteria

Tuberculosis (TB) is the worldwide leading infectious killer due to a single pathogen and increasing antimicrobial resistance (AMR) makes it imperative to discover and develop new drugs with novel modes of action (MoAs) to treat TB infections. Phenotypic screening of chemical libraries has proven effective at identifying new compounds against bacterial pathogens. However, a major limitation of sta...

In Defense of Cosine Similarity: Normalization Eliminates the Gauge Freedom

Steck, Ekanadham, and Kallus [arXiv:2403.05440] demonstrate that cosine similarity of learned embeddings from matrix factorization models can be rendered arbitrary by a diagonal ``gauge'' matrix $D$. Their result is correct and important for practitioners who compute cosine similarity on embeddings trained with dot-product objectives. However, we argue that their conclusion, cautioning against cos...

Feature-based in-silico model to predict the Mycobacterium tuberculosis bedaquiline phenotype associated with Rv0678 variants

Bedaquiline resistance is emerging globally and threatens the effectiveness of the novel short all-oral regimens for rifampicin-resistant tuberculosis...

DeepRed: an architecture for redshift estimation

Estimating redshift is a central task in astrophysics, but its measurement is costly and time-consuming. In addition, current image-based methods are ...

Beyond the Unit Hypersphere: Embedding Magnitude in Contrastive Learning

Cosine similarity is prevalent in contrastive learning, yet it makes an implicit assumption: embedding magnitude is noise. Prior work occasionally fou...

Score-based diffusion models for diffuse optical tomography with uncertainty quantification

Score-based diffusion models are a recently developed framework for posterior sampling in Bayesian inverse problems with a state-of-the-art performanc...

BIG-TB: A benchmark for evaluating prediction and interpretability of sequence-based machine learning using *Mycobacterium tuberculosis* genomes

Foundation models aim to learn useful representations of biological sequences. However, the applicability of these representations for a wide range of...

Deep Learning-Based Spatial Immunoprofiling of Multiplex Immunofluorescence Images Distinguishes Tuberculosis Disease States in Diversity Outbred Mice

Tuberculosis (TB), caused by Mycobacterium tuberculosis (M.tb), remains a major global health challenge, with approximately 10.8 million new cases and...

MorphXAI: An Explainable Framework for Morphological Analysis of Parasites in Blood Smear Images

Parasitic infections remain a pressing global health challenge, particularly in low-resource settings where diagnosis still depends on labor-intensive...

GEOGRAPHIC DOMAIN SHIFT PRECIPITATES DIVERGENT FAILURE MODES IN DEEP LEARNING BASED TUBERCULOSIS SCREENING: A MULTI-NATIONAL EXTERNAL VALIDATION STUDY

Background: Deep learning algorithms for tuberculosis (TB) screening frequently achieve radiologist-level performance during internal evaluation, yet ...

[Tongue swabs: a novel tool for tuberculosis screening].

Tuberculosis (TB) remains a significant global public health threat. Achieving the 2035 target for TB elimination requires interrupting its community ...

GNN-ViTCap: GNN-Enhanced Multiple Instance Learning with Vision Transformers for Whole Slide Image Classification and Captioning

Microscopic assessment of histopathology images is vital for accurate cancer diagnosis and treatment. Whole Slide Image (WSI) classification and cap...

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models

The use of generative artificial intelligence (AI) models is becoming ubiquitous in many fields. Though progress continues to be made, general purpo...

Deep Learning Models for CT Segmentation of Invasive Pulmonary Aspergillosis, Mucormycosis, Bacterial Pneumonia and Tuberculosis: A Multicentre Study.

BACKGROUND: The differential diagnosis of invasive pulmonary aspergillosis (IPA), pulmonary mucormycosis (PM), bacterial pneumonia (BP) and pulmonary ...

MedPrompt: LLM-CNN Fusion with Weight Routing for Medical Image Segmentation and Classification

Current medical image analysis systems are typically task-specific, requiring separate models for classification and segmentation, and lack the flex...

Bibliometric analysis of research on spinal tuberculosis in last 5 years.

BACKGROUND: Spinal tuberculosis (TB), also known as Pott's spine, remains a significant global health issue, particularly in regions with a high TB bu...

The Cambrian Explosion of Mixed-Precision Matrix Multiplication for Quantized Deep Learning Inference

Recent advances in deep learning (DL) have led to a shift from traditional 64-bit floating point (FP64) computations toward reduced-precision format...

VQC-MLPNet: An Unconventional Hybrid Quantum-Classical Architecture for Scalable and Robust Quantum Machine Learning

Variational Quantum Circuits (VQCs) offer a novel pathway for quantum machine learning, yet their practical application is hindered by inherent limi...

Machine learning-guided fabrication of carbon dot-pepsin nano-conjugates for enhanced bioimaging, synergistic drug delivery, and visible light-induced photosensitization.

Carbon dots (CDs) are emerging as next-generation bioimaging agents due to their strong fluorescence, photobleaching resistance, and biocompatibility....

On Finetuning Tabular Foundation Models

Foundation models are an emerging research direction in tabular deep learning. Notably, TabPFNv2 recently claimed superior performance over traditio...