Role of Machine Learning Assisted Biosensors in Point-of-Care-Testing For Clinical Decisions.

Point-of-Care-Testing (PoCT) has emerged as an essential component of modern healthcare, providing rapid, low-cost, and simple diagnostic options. The integration of Machine Learning (ML) into biosensors has ushered in a new era of innovation in the field of PoCT. This article investigates the numerous uses and transformational possibilities of ML in improving biosensors for PoCT.

Reconfigurable Logic-in-Memory Constructed Using an Organic Antiambipolar Transistor.

We demonstrate an electrically reconfigurable two-input logic-in-memory (LIM) using a dual-gate-type organic antiambipolar transistor (DG-OAAT). The attractive feature of this device is that a phthalocyanine-cored star-shaped polystyrene is used as a nano-floating gate, which enables the electrical switching of individual logic circuits and stores the circuit information by the nonvolatile memory effect. First, the DG-OAAT exhibited Λ-shaped transfer curves with hysteresis by sweeping the bottom-gate voltage.

Optically Controllable Organic Logic-in-Memory: An Innovative Approach toward Ternary Data Processing and Storage.

Logic-in-memory (LIM) has emerged as an energy-efficient computing technology, as it integrates logic and memory operations in a single device architecture. Herein, a concept of ternary LIM is established. First, a p-type 2,7-dioctyl[1]benzothieno[3,2-][1]benzothiophene (C8-BTBT) transistor is combined with an n-type PhCH-benzo[de]isoquinolino[1,8-gh]quinolone diimide (PhC2-BQQDI) transistor to obtain a binary memory inverter, in which a zinc phthalocyanine-cored polystyrene (ZnPc-PS) layer serves as a floating gate.